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  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted by number of followers
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 314)
Control Systems     Hybrid Journal   (Followers: 252)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 202)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 194)
Electronics     Open Access   (Followers: 138)
Advances in Electronics     Open Access   (Followers: 132)
Electronic Design     Partially Free   (Followers: 129)
Electronics For You     Partially Free   (Followers: 128)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 120)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 91)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 89)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 88)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 84)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 84)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 81)
IET Power Electronics     Open Access   (Followers: 70)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 67)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 63)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 62)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 58)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 53)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 53)
Advances in Power Electronics     Open Access   (Followers: 49)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 45)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 45)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 41)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 35)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 34)
IET Microwaves, Antennas & Propagation     Open Access   (Followers: 34)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 30)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 28)
Electronics Letters     Open Access   (Followers: 28)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 27)
Microelectronics and Solid State Electronics     Open Access   (Followers: 27)
International Journal of Power Electronics     Hybrid Journal   (Followers: 24)
International Journal of Aerospace Innovations     Full-text available via subscription   (Followers: 24)
Journal of Sensors     Open Access   (Followers: 23)
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 22)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 20)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 19)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 18)
Journal of Artificial Intelligence     Open Access   (Followers: 18)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 17)
IET Wireless Sensor Systems     Open Access   (Followers: 17)
Circuits and Systems     Open Access   (Followers: 16)
Machine Learning with Applications     Full-text available via subscription   (Followers: 15)
Archives of Electrical Engineering     Open Access   (Followers: 15)
International Journal of Control     Hybrid Journal   (Followers: 14)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 14)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 14)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 13)
Advances in Microelectronic Engineering     Open Access   (Followers: 13)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 12)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 12)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 11)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 11)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 11)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 11)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 11)
Open Journal of Antennas and Propagation     Open Access   (Followers: 10)
IETE Journal of Research     Open Access   (Followers: 10)
Solid-State Electronics     Hybrid Journal   (Followers: 10)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 10)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
IETE Technical Review     Open Access   (Followers: 9)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 9)
Nature Electronics     Hybrid Journal   (Followers: 9)
Superconductivity     Full-text available via subscription   (Followers: 9)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 9)
Batteries     Open Access   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 8)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 8)
International Journal of Antennas and Propagation     Open Access   (Followers: 8)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 8)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 8)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 8)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 8)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 8)
China Communications     Full-text available via subscription   (Followers: 8)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Power Electronic Devices and Components     Open Access   (Followers: 7)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 7)
Nanotechnology, Science and Applications     Open Access   (Followers: 7)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 6)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 6)
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access   (Followers: 6)
International Journal of Electronics     Hybrid Journal   (Followers: 6)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 6)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
Journal of Power Electronics     Hybrid Journal   (Followers: 6)
Annals of Telecommunications     Hybrid Journal   (Followers: 6)
Electronic Markets     Hybrid Journal   (Followers: 6)
Energy Storage Materials     Full-text available via subscription   (Followers: 6)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 5)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
Journal of Optoelectronics Engineering     Open Access   (Followers: 5)
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 5)
Journal of Field Robotics     Hybrid Journal   (Followers: 5)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
IEEE Pulse     Hybrid Journal   (Followers: 5)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 4)
Networks: an International Journal     Hybrid Journal   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal   (Followers: 4)
Advanced Materials Technologies     Hybrid Journal   (Followers: 4)
Frontiers in Electronics     Open Access   (Followers: 4)
Wireless and Mobile Technologies     Open Access   (Followers: 4)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 4)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 4)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 4)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 4)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Informatik-Spektrum     Hybrid Journal   (Followers: 3)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 3)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 3)
Advancing Microelectronics     Hybrid Journal   (Followers: 3)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 3)
IETE Journal of Education     Open Access   (Followers: 3)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Sensors International     Open Access   (Followers: 3)
e-Prime : Advances in Electrical Engineering, Electronics and Energy     Open Access   (Followers: 3)
EPJ Quantum Technology     Open Access   (Followers: 3)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 3)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 2)
ACS Applied Electronic Materials     Open Access   (Followers: 2)
IET Smart Grid     Open Access   (Followers: 2)
Energy Storage     Hybrid Journal   (Followers: 2)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 2)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal   (Followers: 2)
Journal of Information and Telecommunication     Open Access   (Followers: 2)
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 2)
Journal of Semiconductors     Full-text available via subscription   (Followers: 2)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 2)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Journal of Nuclear Cardiology     Hybrid Journal   (Followers: 2)
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 1)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 1)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Електротехніка і Електромеханіка     Open Access   (Followers: 1)
Open Electrical & Electronic Engineering Journal     Open Access   (Followers: 1)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 1)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Transactions on Cryptographic Hardware and Embedded Systems     Open Access   (Followers: 1)
International Journal of Hybrid Intelligence     Hybrid Journal   (Followers: 1)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
Edu Elektrika Journal     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 1)
Automatika : Journal for Control, Measurement, Electronics, Computing and Communications     Open Access  
npj Flexible Electronics     Open Access  
Elektronika ir Elektortechnika     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access  
IEEE Solid-State Circuits Letters     Hybrid Journal  
IEEE Open Journal of Industry Applications     Open Access  
IEEE Open Journal of the Industrial Electronics Society     Open Access  
IEEE Open Journal of Circuits and Systems     Open Access  
Journal of Electronic Science and Technology     Open Access  
Solid State Electronics Letters     Open Access  
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Journal of Engineered Fibers and Fabrics     Open Access  
Jurnal Teknologi Elektro     Open Access  
IET Nanodielectrics     Open Access  
Elkha : Jurnal Teknik Elektro     Open Access  
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Jurnal Teknik Elektro     Open Access  
IACR Transactions on Symmetric Cryptology     Open Access  
Acta Electronica Malaysia     Open Access  
Bioelectronics in Medicine     Hybrid Journal  
Chinese Journal of Electronics     Open Access  
Problemy Peredachi Informatsii     Full-text available via subscription  
Technical Report Electronics and Computer Engineering     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Visión Electrónica : algo más que un estado sólido     Open Access  
Telematique     Open Access  
International Journal of Nanoscience     Hybrid Journal  
International Journal of High Speed Electronics and Systems     Hybrid Journal  
Semiconductors and Semimetals     Full-text available via subscription  

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Similar Journals
Journal Cover
IEEE Transactions on Automatic Control
Journal Prestige (SJR): 3.433
Citation Impact (citeScore): 6
Number of Followers: 67  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-9286
Published by IEEE Homepage  [228 journals]
  • IEEE Transactions on Automatic Control Publication Information

    • Free pre-print version: Loading...

      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • IEEE Control Systems Society Information

    • Free pre-print version: Loading...

      Abstract: Presents a listing of the editorial board, board of governors, current staff, committee members, and/or society editors for this issue of the publication.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Decentralized Primal-Dual Method for Constrained Minimization of a
           Strongly Convex Function

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      Authors: Erfan Yazdandoost Hamedani;Necdet Serhat Aybat;
      Pages: 5682 - 5697
      Abstract: We propose decentralized primal-dual methods for cooperative multiagent consensus optimization problems over both static and time-varying communication networks, where only local communications are allowed. The objective is to minimize the sum of agent-specific convex functions over conic constraint sets defined by agent-specific nonlinear functions; hence, the optimal consensus decision should lie in the intersection of these private sets. Under the strong convexity assumption, we provide convergence rates for suboptimality, infeasibility, and consensus violation in terms of the number of communications required; examine the effect of underlying network topology on the convergence rates.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Formal Safety Net Control Using Backward Reachability Analysis

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      Authors: Bastian Schürmann;Moritz Klischat;Niklas Kochdumper;Matthias Althoff;
      Pages: 5698 - 5713
      Abstract: Ensuring safety is crucial for the successful deployment of autonomous systems, such as self-driving vehicles, unmanned aerial vehicles, and robots acting close to humans. While there exist many controllers that optimize certain criteria, such as energy consumption, comfort, or low wear, they are usually not able to guarantee safety at all times for constrained nonlinear systems affected by disturbances. Many controllers providing safety guarantees, however, have no optimal performance. The idea of this article is, therefore, to synthesize a formally correct controller that serves as a safety net for an unverified, optimal controller. This way, most of the time, the optimal controller is in charge and leads to a desired, optimal control performance. The safety controller constantly monitors the actions of the optimal controller and takes over if the system would become unsafe. The safety controller utilizes a novel concept of backward reachable set computation, where we avoid the need of computing underapproximations of reachable sets. We have further developed a new approach that analytically describes reachable sets, making it possible to efficiently maximize the size of the backward reachable set. We demonstrate our approach by a numerical example from autonomous driving.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Boundary Stability Criterion for a Nonlinear Axially Moving Beam

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      Authors: Yi Cheng;Yuhu Wu;Bao-Zhu Guo;
      Pages: 5714 - 5729
      Abstract: This article deals with, in the framework of absolute stability, boundary stabilization for a nonlinear axially moving beam under boundary velocity feedback controls. The nonlinear boundary control that satisfies a slope-sector condition covering many types of nonlinear control schemes is a negative feedback of the transverse velocity at the right eyelet of the moving beam. Under the nonlinear control scheme, the well-posedness of the nonlinear partial differential equation, which depends continuously on the initial value is investigated by means of the Faedo–Galerkin approximation and priori estimates. By exploiting the integral-type multiplier method, the exponential stability of the closed-loop system is established, where a novel energy like function is constructed. The numerical simulation examples using the finite element method are presented to illustrate the effectiveness of the established criterion of the controller.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Exact Detectability of Discrete-Time and Continuous-Time Linear Stochastic
           Systems: A Unified Approach

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      Authors: Vasile Drăgan;Eduardo Fontoura Costa;Ioan-Lucian Popa;Samir Aberkane;
      Pages: 5730 - 5745
      Abstract: This article is devoted to the problem of detectability of a large class of linear stochastic systems with time varying coefficients simultaneously affected by state multiplicative white noise perturbations and Markovian switching. The main contribution of this article is to propose a Popov–Belevich–Hautus-type test, which is equivalent to the detectability of the considered stochastic systems in the sense that all unstable modes produce some nonzero output. The proposed setting unifies in some sense the discrete-time and continuous-time ones, dissimilarly to the vast majority of existing works that study discrete and continuous time separately.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Topology Learning of Linear Dynamical Systems With Latent Nodes Using
           Matrix Decomposition

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      Authors: Mishfad Shaikh Veedu;Harish Doddi;Murti V. Salapaka;
      Pages: 5746 - 5761
      Abstract: In this article, we present a novel approach to reconstruct the topology of networked linear dynamical systems with latent nodes. The network is allowed to have directed loops and bi-directed edges. The main approach relies on the unique decomposition of the inverse of power spectral density matrix (IPSDM) obtained from observed nodes as a sum of sparse and low-rank matrices. We provide conditions and methods for decomposing the IPSDM into sparse and low-rank components. The sparse component yields moral graph (MG) associated with the observed nodes, and the low-rank component retrieves parents, children and spouses (the Markov Blanket) of the hidden nodes. The article provides necessary and sufficient conditions for the unique decomposition of a given skew symmetric matrix into sum of a sparse skew symmetric and a low-rank skew symmetric matrices. For a large class of systems, the unique decomposition of imaginary part of the IPSDM of observed nodes, a skew symmetric matrix, into the sparse and the low-rank components is sufficient to identify the MG of the observed nodes as well as the Markov Blanket of latent nodes. For a large class of systems, all spurious links in the MG formed by the observed nodes can be identified. Assuming conditions on hidden nodes required for identifiability, links between hidden and observed nodes can be reconstructed, thus retrieving the exact topology of the network from the IPSDM. Moreover, for finite data, we provide bounds on entry-wise distance between the true and the estimated IPSDMs.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Distributionally Robust Optimization Based Method for Stochastic Model
           Predictive Control

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      Authors: Bin Li;Yuan Tan;Ai-Guo Wu;Guang-Ren Duan;
      Pages: 5762 - 5776
      Abstract: Two stochastic model predictive control algorithms, which are referred to as distributionally robust model predictive control algorithms, are proposed in this article for a class of discrete linear systems with unbounded noise. Participially, chance constraints are imposed on both of the state and the control, which makes the problem more challenging. Inspired by the ideas from distributionally robust optimization (DRO), two deterministic convex reformulations are proposed for tackling the chance constraints. Rigorous computational complexity analysis is carried out to compare the two proposed algorithms with the existing methods. Recursive feasibility and convergence are proven. Simulation results are provided to show the effectiveness of the proposed algorithms.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Limiting Behavior of Hybrid Time-Varying Systems

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      Authors: Ti-Chung Lee;Ying Tan;Iven Mareels;
      Pages: 5777 - 5792
      Abstract: Checking uniform attractivity of a time-varying dynamic system without a strict Lyapunov function is challenging as it requires the characterization of the limiting behavior of a set of trajectories. In the context of hybrid nonlinear time-varying systems, characterizing such limiting or convergent behaviors is even harder due to the complexity stemming from both continuous-time variations as well as discrete-time jumps. In this article, an extension of the standard hybrid time domain is introduced to define limiting behaviors, using set convergence, when time approaches either positive infinity or negative infinity. In particular, it is shown how to characterize limiting behaviors under the condition that an output signal approaches zero. Such limiting behaviors and their associated limiting systems can be used to verify uniform global attractivity. Particularly, a generalization of the classic Krasovskii–LaSalle theorem is obtained for hybrid time-varying systems. Two examples are used to demonstrate the effectiveness of the results.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Agent Transformation of Bayesian Games

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      Authors: Yuhu Wu;Shuting Le;Kuize Zhang;Xi-Ming Sun;
      Pages: 5793 - 5808
      Abstract: A new transformation that converts a Bayesian game to a so-called ex-ante agent game (a normal-form game) is proposed. Differently from the existing transformation proposed by R. Selten that changes a Bayesian game to an interim agent game (also a pure normal-form game), we prove that the new transformation preserves potentiality. In addition, there is a nonpotential Bayesian game whose ex-ante agent game is potential. We also prove that there is one-to-one correspondence between pure Bayesian Nash equilibria (BNE) of Bayesian games (if one exists) and pure Nash equilibria (NE) of the resulting ex-ante agent games. Then, we provide a sufficient and necessary condition for a Bayesian game to have an ex-ante agent potential game. By using these results, one can transform pure BNE seeking in Bayesian games to pure NE seeking in their ex-ante agent games [by using the potential functions of the ex-ante agent games (if one exists)], where previously pure BNE seeking in Bayesian games by using potential functions can only be done in Bayesian potential games (BPGs). Particularly, we prove for two-player games that BPGs are exactly the Bayesian games having ex-ante agent potential games. Furthermore, by using the semi-tensor product of matrices, a potential equation for finite Bayesian games is developed. Based on the potential equation, algorithms for verifying potentiality and for searching pure BNE in finite Bayesian games are designed. Finally, the results are applied to a routing problem with incomplete information.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • On the Complexity of Sequential Incentive Design

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      Authors: Yagiz Savas;Vijay Gupta;Ufuk Topcu;
      Pages: 5809 - 5824
      Abstract: In many scenarios, a principal dynamically interacts with an agent and offers a sequence of incentives to align the agent’s behavior with a desired objective. This article focuses on the problem of synthesizing an incentive sequence that, once offered, induces the desired agent behavior even when the agent’s intrinsic motivation is unknown to the principal. We model the agent’s behavior as a Markov decision process, express its intrinsic motivation as a reward function, which belongs to a finite set of possible reward functions, and consider the incentives as additional rewards offered to the agent. We first show that the behavior modification problem (BMP), i.e., the problem of synthesizing an incentive sequence that induces a desired agent behavior at minimum total cost to the principal, is PSPACE-hard. We then show that two NP-complete variants of the BMP can be obtained by imposing certain restrictions on the incentive sequences available to the principal. We also provide a sufficient condition on the set of possible reward functions under which the BMP can be solved via linear programming. Finally, we propose two algorithms to compute globally and locally optimal solutions to the NP-complete variants of the BMP.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • The Covariance Extension Equation: A Riccati-Type Approach to Analytic
           Interpolation

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      Authors: Yufang Cui;Anders Lindquist;
      Pages: 5825 - 5840
      Abstract: Analytic interpolation problems with rationality and derivative constraints are ubiquitous in systems and control. This article provides a new method for such problems, both in the scalar and matrix case, based on a nonstandard Riccati-type equation. The rank of the solution matrix is the same as the degree of the interpolant, thus providing a natural approach to model reduction. A homotopy continuation method is presented and applied to some problems in modeling and robust control. We also address a question on the positive degree of a covariance sequence originally posed by Kalman.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Integral-Input-to-State Stability of Switched Nonlinear Systems Under Slow
           Switching

    • Free pre-print version: Loading...

      Authors: Shenyu Liu;Antonio Russo;Daniel Liberzon;Alberto Cavallo;
      Pages: 5841 - 5855
      Abstract: In this article we study integral-input-to-state stability (iISS) of nonlinear switched systems with jumps. We demonstrate by examples that iISS is not always preserved under slow enough dwell time switching, and then we present sufficient conditions for iISS to be preserved under slow switching. These conditions involve, besides a sufficiently large dwell time, some additional properties of comparison functions characterizing iISS of the individual modes. When the sufficient conditions that guarantee iISS are only partially satisfied, we are then able to conclude weaker variants of iISS, also introduced in this work. As an illustration, we show that switched systems with bilinear zero-input-stable modes are always iISS under sufficiently large dwell time.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Controller Reduction for Nonlinear Systems by Generalized Differential
           Balancing

    • Free pre-print version: Loading...

      Authors: Yu Kawano;
      Pages: 5856 - 5871
      Abstract: In this article, we aim at developing computationally tractable methods for nonlinear model/controller reduction. Recently, model reduction by generalized differential (GD) balancing has been proposed for nonlinear systems with constant input-vector fields and linear output functions. First, we study incremental properties in the GD balancing framework. Next, based on these analyses, we provide GD linear quadratic Gaussian (LQG) balancing and GD $H_infty$-balancing as controller reduction methods for nonlinear systems by focusing on linear feedback and observer gains. Especially for GD $H_infty$-balancing, we clarify when the closed-loop system consisting of the full-order system and a reduced-order controller is exponentially stable. All provided methods for controller reduction can be relaxed to linear matrix inequalities (LMIs).
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • System Monotonicity and Subspace Tracking: A Geometric Perspective of the
           Frisch–Shapiro Scheme

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      Authors: Di Zhao;Sei Zhen Khong;Li Qiu;
      Pages: 5872 - 5884
      Abstract: The Shapiro scheme, together with the closely related Frisch–Kalman scheme, has been an important approach to system identification and statistical analysis. A longstanding result on this scheme, known as the Shapiro theorem, is both informative and significant. This article imparts a geometric understanding to the Shapiro theorem and generalizes it to the asymmetric setting using the notion of cone-invariance. In particular, we establish the equivalence between two important properties of a real-valued square matrix—irreducible orthant-invariance and simplicity of its dominant eigenvalue under arbitrary diagonal perturbations. The result can be regarded as a converse Perron–Frobenius theorem. Furthermore, we investigate two applications of the proposed result in systems and control, namely, characterization of irreducibly orthant-monotone nonlinear systems and subspace tracking via decentralized control. We also extend the established result to accommodating polyhedral cones and obtain several insights.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Stochastic MPC With Dynamic Feedback Gain Selection and Discounted
           Probabilistic Constraints

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      Authors: Shuhao Yan;Paul J. Goulart;Mark Cannon;
      Pages: 5885 - 5899
      Abstract: This article considers linear discrete-time systems with additive disturbances and designs a model predictive control (MPC) law incorporating a dynamic feedback gain to minimize a quadratic cost function subject to a single chance constraint. The feedback gain is selected online, and we provide two selection methods based on minimizing upper bounds on predicted costs. The chance constraint is defined as a discounted sum of violation probabilities on an infinite horizon. By penalizing violation probabilities close to the initial time and assigning violation probabilities in the far future with vanishingly small weights, this form of constraints allows for an MPC law with guarantees of recursive feasibility without a boundedness assumption on the disturbance. A computationally convenient MPC optimization problem is formulated using Chebyshev’s inequality, and we introduce an online constraint-tightening technique to ensure recursive feasibility. The closed-loop system is guaranteed to satisfy the chance constraint and a quadratic stability condition. With dynamic feedback gain selection, the closed-loop cost is reduced and conservativeness of Chebyshev’s inequality is mitigated. Also, a larger feasible set of initial conditions can be obtained. Numerical simulations are given to show these results.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Sharp Estimate on the Transient Time of Distributed Stochastic Gradient
           Descent

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      Authors: Shi Pu;Alex Olshevsky;Ioannis Ch. Paschalidis;
      Pages: 5900 - 5915
      Abstract: This article is concerned with minimizing the average of $n$ cost functions over a network, in which agents may communicate and exchange information with each other. We consider the setting where only noisy gradient information is available. To solve the problem, we study the distributed stochastic gradient descent (DSGD) method and perform a nonasymptotic convergence analysis. For strongly convex and smooth objective functions, in expectation, DSGD asymptotically achieves the optimal network-independent convergence rate compared to centralized stochastic gradient descent. Our main contribution is to characterize the transient time needed for DSGD to approach the asymptotic convergence rate. Moreover, we construct a “hard” optimization problem that proves the sharpness of the obtained result. Numerical experiments demonstrate the tightness of the theoretical results.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Homogeneity, Forward Completeness, and Global Stabilization of a Family of
           Time-Delay Nonlinear Systems by Memoryless Non-Lipschitz Continuous
           Feedback

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      Authors: Congran Zhao;Wei Lin;
      Pages: 5916 - 5931
      Abstract: For a family of genuinely nonlinear systems with delays in the input and state, global strong stabilization (GSS) in the sense of Kurzweil is shown to be possible by memoryless state and/or output feedback under two conditions: 1) The input delay is within an appropriate range although the state delays can be sufficiently large; 2) the time-delay bounding system is homogeneous of degree zero and has a lower triangular structure. The proof is based on the Lyapunov–Krasovskii functional theorem combined with the homogeneous domination philosophy. Using the emulation approach, we design memoryless homogeneous state and output feedback controllers, respectively, achieving GSS of the time-delay closed-loop systems with severe nonlinearity. Extensions to a wider class of time-delay nonlinear systems in the Hessenberg form are also given. Examples and counter-examples presented in this article illustrate not only the necessity of the homogeneous growth conditions but also the significance of the memoryless non-Lipschitz continuous feedback control strategies.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Sufficient and Necessary Graphical Conditions for MISO Identification in
           Networks With Observational Data

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      Authors: Sina Jahandari;Donatello Materassi;
      Pages: 5932 - 5947
      Abstract: This article addresses the problem of consistently identifying a single transfer function in a network of dynamic systems using only observational data. It is assumed that the topology is partially known, the forcing inputs are not measured, and that only a subset of the nodes outputs is accessible. The developed technique is applicable to scenarios encompassing confounding variables and feedback loops, which are complicating factors potentially introducing bias in the estimate of the transfer function. The results are based on the prediction of the output node using the input node along with a set of additional auxiliary variables which are selected only from the observed nodes. Similar prediction error methods provide only sufficient conditions for the appropriate choice of auxiliary variables and assume a priori information about the location of strictly causal operators in the network. In this article, such an a priori knowledge is not required. A most remarkable feature of our approach is that the conditions for the selection of the auxiliary variables are purely graphical. Furthermore, within single-output prediction methods, such conditions are proven to be necessary and sufficient to consistently identify all networks with a given topology. A fundamental consequence of this characterization is to enable the search of a set of auxiliary variables minimizing a suitable cost function for single-output prediction error identification. In the article, we suggest possible approaches to tackle such optimal identification problems.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Q-Learning With Uniformly Bounded Variance

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      Authors: Adithya M. Devraj;Sean P. Meyn;
      Pages: 5948 - 5963
      Abstract: Sample complexity bounds are a common performance metric in the reinforcement learning literature. In the discounted cost, infinite horizon setting, all of the known bounds can be arbitrarily large, as the discount factor approaches unity. These results seem to imply that a very large number of samples is required to achieve an epsilon-optimal policy. The objective of the present work is to introduce a new class of algorithms that have sample complexity uniformly bounded over all discount factors. One may argue that this is impossible, due to a recent min–max lower bound. The explanation is that these prior bounds concern value function approximation and not policy approximation. We show that the asymptotic covariance of the tabular Q-learning algorithm with an optimized step-size sequence is a quadratic function of a factor that goes to infinity, as discount factor approaches 1; an essentially known result. The new relative Q-learning algorithm proposed here is shown to have asymptotic covariance that is uniformly bounded over all discount factors.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • On Self-Learning Mechanism for the Output Regulation of Second-Order
           Affine Nonlinear Systems

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      Authors: Haiwen Wu;Dabo Xu;Bayu Jayawardhana;
      Pages: 5964 - 5979
      Abstract: This article studies global robust output regulation of second-order nonlinear systems with input disturbances that encompass the fully-actuated Euler–Lagrange systems. We assume the availability of relative output (w.r.t. a family of reference signals) and output derivative measurements. Based on a specific separation principle and self-learning mechanism, we develop an internal model-based controller that does not require a priori knowledge of reference and disturbance signals and it only assumes that the kernels of these signals are a family of exosystems with unknown parameters (e.g., amplitudes, frequencies, or time periods). The proposed control framework has a self-learning mechanism that extricates itself from requiring absolute position measurement nor precise knowledge of the feedforward kernel signals. By requiring the high-level task/trajectory planner to use the same class of kernels in constraining the trajectories, the proposed low-level controller is able to learn the desired trajectories, to suppress the disturbance signals, and to adapt itself to the uncertain plant parameters. The framework enables a plug-and-play control mechanism in both levels of control.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Linear Reduced-Order Model Predictive Control

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      Authors: Joseph Lorenzetti;Andrew McClellan;Charbel Farhat;Marco Pavone;
      Pages: 5980 - 5995
      Abstract: Model predictive controllers use dynamics models to solve constrained optimal control problems. However, computational requirements for real-time control have limited their use to systems with low-dimensional models. Nevertheless, high-dimensional models arise in many settings, for example, discretization methods for generating finite-dimensional approximations to partial differential equations can result in models with thousands to millions of dimensions. In such cases, reduced-order models (ROMs) can significantly reduce computational requirements, but model approximation error must be considered to guarantee controller performance. In this article, a reduced-order model predictive control (ROMPC) scheme is proposed to solve robust, output feedback, constrained optimal control problems for high-dimensional linear systems. Computational efficiency is obtained by using projection-based ROMs, and guarantees on robust constraint satisfaction and stability are provided. The performance of the approach is demonstrated in simulation for several examples, including an aircraft control problem leveraging an inviscid computational fluid dynamics model with dimension 998 930.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • On the Convergence of Overlapping Schwarz Decomposition for Nonlinear
           Optimal Control

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      Authors: Sen Na;Sungho Shin;Mihai Anitescu;Victor M. Zavala;
      Pages: 5996 - 6011
      Abstract: We study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems (OCPs). The algorithm decomposes the time domain into a set of overlapping subdomains, and solves all subproblems defined over subdomains in parallel. The convergence is attained by updating primal-dual information at the boundaries of overlapping subdomains. We show that the algorithm exhibits local linear convergence, and that the convergence rate improves exponentially with the overlap size. We also establish global convergence results for a general quadratic programming, which enables the application of the Schwarz scheme inside second-order optimization algorithms (e.g., sequential quadratic programming). The theoretical foundation of our convergence analysis is a sensitivity result of nonlinear OCPs, which we call “exponential decay of sensitivity” (EDS). Intuitively, EDS states that the impact of perturbations at domain boundaries (i.e., initial and terminal time) on the solution decays exponentially as one moves into the domain. Here, we expand a previous analysis available in the literature by showing that EDS holds for both primal and dual solutions of nonlinear OCPs, under uniform second-order sufficient condition, controllability condition, and boundedness condition. We conduct experiments with a quadrotor motion planning problem and a partial differential equations (PDE) control problem to validate our theory, and show that the approach is significantly more efficient than alternating direction method of multipliers and as efficient as the centralized interior-point solver.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Robust Control Performance for Open Quantum Systems

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      Authors: Sophie G. Schirmer;Frank C. Langbein;Carrie Ann Weidner;Edmond Jonckheere;
      Pages: 6012 - 6024
      Abstract: Robust performance of control schemes for open quantum systems is investigated under classical uncertainties in the generators of the dynamics and nonclassical uncertainties due to decoherence and initial state preparation errors. A formalism is developed to measure performance based on the transmission of a dynamic perturbation or initial state preparation error to the quantum state error. This makes it possible to apply tools from classical robust control, such as structured singular value analysis. A difficulty arising from the singularity of the closed-loop Bloch equations for the quantum state is overcome by introducing the #-inversion lemma, a specialized version of the matrix inversion lemma. Under some conditions, this guarantees continuity of the structured singular value at $s = 0$. Additional difficulties occur when symmetry gives rise to multiple open-loop poles, which under symmetry-breaking unfold into single eigenvalues. The concepts are applied to systems subject to pure decoherence and a general dissipative system example of two qubits in a leaky cavity under laser driving fields and spontaneous emission. A nonclassical performance index, steady-state entanglement quantified by the concurrence, a nonlinear function of the system state, is introduced. Simulations confirm a conflict between entanglement, its log-sensitivity and stability margin under decoherence.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Distributed Average Tracking With Incomplete Measurement Under a
           Weight-Unbalanced Digraph

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      Authors: Arijit Sen;Soumya Ranjan Sahoo;Mangal Kothari;
      Pages: 6025 - 6037
      Abstract: During the implementation of a cooperative algorithm, information about the agents’ velocity may be unavailable due to the space constraint and availability of sensors. Thus, it gives rise to the design of distributed average tracking (DAT) algorithms without using agents’ velocity measurements. These are denoted as velocity-free DAT problems. The existing literature has addressed such problems in the presence of an undirected graph for the reference signals with bounded position, velocity, and acceleration differences. We propose a velocity-free DAT algorithm under a weight-unbalanced strongly-connected digraph that represents the most general network structure for achieving DAT. Additionally, the proposed algorithm works for a broader range of time-varying references, having bounded acceleration differences among themselves. Linear stability theory is used to establish uniform ultimate boundedness of the errors for bounded acceleration differences. Asymptotic convergence of the errors is guaranteed for converging acceleration differences. Unlike the existing works, our DAT algorithm does not need any update law for the gains. Thus, the approach is computationally efficient. Numerical simulations with the comparison with the state-of-the-art demonstrate the performance of our algorithm over a wider range of time-varying references under weight-unbalanced graph.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • An Adaptive Continuous-Time Algorithm for Nonsmooth Convex Resource
           Allocation Optimization

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      Authors: Wenwen Jia;Na Liu;Sitian Qin;
      Pages: 6038 - 6044
      Abstract: This article develops a novel continuous-time algorithm based on the idea of adaptive strategy for solving a resource allocation optimization with nonsmooth objective functions and constraints over multiagent network. It is proved that the state solution is globally bounded and finally converges to an optimal solution to the nonsmooth convex resource allocation problem. Compared with the existing algorithms, the strong/strict convexity of the objective function is relaxed and only convexity is required. Moreover, by employing an exact penalty approach for the distributed optimization, the primal-dual variables is avoided to introduce. Therefore, the proposed algorithm has a simple structure with low dimensionality of state variables. To show the effectiveness and practicability of the presented algorithm, a numerical example and an application in power system are presented.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Tractable Calculation and Estimation of the Optimal Weighting Matrix for
           ALS Problems

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      Authors: Travis J. Arnold;James B. Rawlings;
      Pages: 6045 - 6052
      Abstract: We study autocovariance least squares (ALS) estimation methods for covariance estimation for linear time-invariant systems. Previous works have posited that calculation of the ALS weighting matrix is intractable unless the number of data points $N_d$ is small because it requires storage of a matrix whose number of elements scales as $N_d^4$. We derive a novel way to compute the weight that avoids this difficulty. In practice, the true optimal weight cannot be calculated because it is a function of the sought covariance matrices. However, our work enables implementation of two novel ALS algorithms that estimate the weight from data. For the purpose of comparison, we also discuss ALS with an arbitrary weight (such as an identity matrix) and present a previously published method for estimating the ALS weight. ALS with an identity weight guarantees unbiased and consistent covariance estimates, but algorithms that estimate the weight from data do not inherit these guarantees. Despite this drawback, we present a numerical example for which the best performing algorithm, iterative estimation of the covariances and the ALS weight, produces covariance estimates with a small amount of bias and a significantly reduced variance compared to all other algorithms.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • When is a Matrix of Dimension Three Similar to a Metzler Matrix'
           Application to Interval Observer Design

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      Authors: Frédéric Mazenc;Olivier Bernard;
      Pages: 6053 - 6059
      Abstract: A simple, necessary, and sufficient condition ensuring that a real matrix of dimension three is similar to a Metzler matrix is exhibited. When this condition is satisfied, a construction of the transfer matrix is given. This construction is used to design an interval observer for a family of continuous-time systems. An example is provided with interval observer design for the so-called love dynamics in the case of limit cycles
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Reconfiguration-Based Fault-Tolerant Control Method for Nonlinear
           Uncertain Systems

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      Authors: Yuanyuan Tu;Dayi Wang;Steven X. Ding;Fangzhou Fu;Wenbo Li;
      Pages: 6060 - 6067
      Abstract: This article addresses reconfiguration-based fault-tolerant control (FTC) with robust guaranteed performance for nonlinear uncertain systems under actuator faults. A PAssive/ACTive combined FTC method is proposed based on reliable control, which synthesizes the advantages of the active and passive FTC and strikes a balance between the performance and complexity of the method. Moreover, the reliability overcost of this method is reduced to balance the system nominal performance and reconfigurability. In this procedure, the $theta$-D method is used to solve the Hamilton–Jacobi–Bellman (HJB) and generalized HJB equations. Effectiveness of the proposed method is verified by a numerical example.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Continuous Multivariable Finite-Time Control Scheme for Double
           Integrator Systems With Bounded Control Input

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      Authors: Bailing Tian;Zhiyu Li;Qun Zong;
      Pages: 6068 - 6073
      Abstract: A multivariable finite-time control algorithm is proposed for double integrator systems with matched disturbances. The remarkable feature of the developed method is to ensure the finite-time stability of the closed-loop system with uniformly bounded control signal with respect to arbitrary initial conditions. The convergence criteria are derived by using the Lyapunov-based techniques, and the upper bound of the control signal can be calculated based on the obtained criteria. Finally, the effectiveness of the proposed algorithm is confirmed by some numerical simulations.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • On Observability of Hybrid Systems

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      Authors: Feng Lin;Le Yi Wang;Wen Chen;Michael P. Polis;
      Pages: 6074 - 6081
      Abstract: Observability of a hybrid system is defined as the ability to determine the continuous state of the system. Whether a hybrid system is observable or not depends on which events can be disabled, which events can be forced, and the connectivity of the discrete states, as well as its continuous dynamics. We model a hybrid system using a hybrid machine that takes into consideration both continuous variables and discrete events. We classify hybrid systems into four classes based on their discrete-event parts. For each class, conditions are derived to check observability. If a hybrid system is not observable, then we check if a weaker version of observability, called $B$-observability, is satisfied. $B$-observability requires that a hybrid system become observable after some finite occurrences of events. Conditions are derived to check $B$-observability. These conditions involve both the discrete-event and continuous-variable parts of hybrid systems. If the continuous-variable part of a system has a constant-$A$ matrix, then the conditions for the continuous-variable part can be simplified. We illustrate the results by an example of a battery management system of an electric vehicle.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Worst-Case Stealthy Innovation-Based Linear Attacks on Remote State
           Estimation Under Kullback–Leibler Divergence

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      Authors: Jun Shang;Hao Yu;Tongwen Chen;
      Pages: 6082 - 6089
      Abstract: With the wide application of cyber-physical systems, stealthy attacks on remote state estimation have attracted increasing research attention. Recently, various stealthy innovation-based linear attack models were proposed, in which the relaxed stealthiness constraint was based on the Kullback–Leibler divergence. This article studies existing innovation-based linear attack strategies with relaxed stealthiness and concludes that all of them provided merely suboptimal solutions. The main reason is some oversight in solving the involved optimization problems: some covariance constraints were not perfectly handled. This article provides the corresponding optimal solutions for those stealthy attacks. Both one-step and holistic optimizations of stealthy attacks are studied, and the worst-case attacks with and without zero-mean constraints are derived analytically, without the necessity to numerically solve semidefinite programming problems.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Sensitivity-Based Data Augmentation Framework for Model Predictive
           Control Policy Approximation

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      Authors: Dinesh Krishnamoorthy;
      Pages: 6090 - 6097
      Abstract: Approximating model predictive control (MPC) policy using expert-based supervised learning techniques requires labeled training datasets sampled from the MPC policy. This is typically obtained by sampling the feasible state space and evaluating the control law by solving the numerical optimization problem offline for each sample. Although the resulting approximate policy can be cheaply evaluated online, generating large training samples to learn the MPC policy can be time-consuming and prohibitively expensive. This is one of the fundamental bottlenecks that limit the design and implementation of MPC policy approximation. This technical article aims to address this challenge, and proposes a novel sensitivity-based data augmentation scheme for direct policy approximation. The proposed approach is based on exploiting the parametric sensitivities to cheaply generate additional training samples in the neighborhood of the existing samples.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Group Consensus of Linear Multiagent Systems Under Nonnegative Directed
           Graphs

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      Authors: Zhongchang Liu;Wing Shing Wong;
      Pages: 6098 - 6105
      Abstract: Group consensus implies reaching multiple groups where agents belonging to the same cluster reach state consensus. This article focuses on linear multiagent systems under nonnegative directed graphs. A new necessary and sufficient condition for ensuring group consensus is derived, which requires the spanning forest of the underlying directed graph and that of its quotient graph induced with respect to a clustering partition to contain equal minimum number of directed trees. This condition is further shown to be equivalent to containing cluster spanning trees, a commonly used topology for the underlying graph in the literature. Under a designed controller gain, lower bound of the overall coupling strength for achieving group consensus is specified. Moreover, the pattern of the multiple consensus states formed by all clusters is characterized when the overall coupling strength is large enough.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • An Asynchronous Gradient Descent Based Method for Distributed Resource
           Allocation With Bounded Variables

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      Authors: Yifan Wang;Qianchuan Zhao;Xuetao Wang;
      Pages: 6106 - 6111
      Abstract: This article considers the distributed resource allocation problem over a network of n agents with individual optimization functions and coupled resource constraints. The optimization variables are bounded for each agent. We propose an asynchronous distributed gradient descent based method, which is able to tackle time-varying communication networks and communication problems. The main ideas are twofold. First, the degree of freedom of the network is reduced to deal with the global constraint. Second, we utilize delay compensation to counteract the delay of asynchronous communication. We prove that the convergence rate is $O(frac{1}{k})$ and analyze both the communication complexity and the time complexity. This method is applied into the parallel pump control problem in HVAC system and shows good numerical results.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Scaling-Function Approach for Distributed Constrained Optimization in
           Unbalanced Multiagent Networks

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      Authors: Fei Chen;Jin Jin;Linying Xiang;Wei Ren;
      Pages: 6112 - 6118
      Abstract: This article aims at developing a scaling-function approach for distributed optimization of unbalanced multiagent networks under convex constraints. The distinguishing feature of the algorithm is that it does not employ agents’ out-degree information, nor does it require the estimation of the left eigenvector, corresponding to the zero eigenvalue, of the Laplacian matrix. Existing approaches for unbalanced networks either demand the knowledge on agents’ out-degrees, which is impractical in applications, where an agent might not be aware of the detection and employment of its information by other agents, or require every agent to be equipped with a network-sized estimator, causing an additional $n^2$ storage and communication cost with $n$ being the network size. The results exhibit an inherent connection between the selection of the scaling factor and the convergence property of the algorithm, among other known factors such as the network topology and the boundedness of the subgradients of the local objective functions. Numerical examples are provided to validate the theoretical findings.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Semiglobal Approach for Stabilizing Nonlinear Systems With State Delays
           by Memoryless Linear Feedback

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      Authors: Yuanjiu Wang;Wei Lin;
      Pages: 6119 - 6126
      Abstract: This article investigates the problem of how to control nonlinear systems with delays in the state by memoryless linear feedback. The notions of semiglobal asymptotic stabilization and sublevel sets are introduced in the context of time-delay systems. With the aid of Razumikhin theorem, we develop a semiglobal design method for the construction of Lyapunov functions, associated sublevel sets, and delay-free linear state feedback laws, step-by-step, achieving semiglobal asymptotic stabilization for time-delay nonlinear systems in a lower triangular form. In contrast to the global stabilization of nonlinear systems with delays in the state, which is usually achieved by dynamic state feedback (Lin and Zhang, 2020), the significance of this work is to point out that a tradeoff of the control objectives, e.g., semiglobal versus global stabilization, makes it possible to control a class of time-delay nonlinear systems by static linear feedback. Extensions to nonlinear systems with globally asymptotically locally expoentially stable (GALES)-like inverse dynamics are also included in this article.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Zonotopic Set-Membership State Estimation for Switched Systems With
           Restricted Switching

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      Authors: Zhongyang Fei;Liu Yang;Xi-Ming Sun;Shunqing Ren;
      Pages: 6127 - 6134
      Abstract: In this article, a novel set-membership state estimation method based on zonotopes is proposed for switched systems subject to unknown-but-bounded disturbance with average dwell time (ADT) switching. By testing the consistency between the system model and measured output, an intersection zonotope is constructed based on mode-dependent and semitime-dependent correction matrix. Then, by constructing semitime-dependent $P$-radius functions, the issue of $L_{infty }$ disturbance attenuation performance for the intersection zonotope is addressed. Finally, a numerical example is presented to illustrate the effectiveness of the proposed approach.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Event-Based Finite-Time Control for High-Order Interconnected Nonlinear
           Systems With Asymmetric Output Constraints

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      Authors: Chang-Chun Hua;Qi-Dong Li;Kuo Li;
      Pages: 6135 - 6142
      Abstract: This article aims to solve the problem of decentralized event-based finite-time control for a class of high-order interconnected nonlinear systems with an asymmetric output constraint. In order to achieve finite-time stability and reduce the update frequency of the controller, a novel controller and its event-trigger mechanism is proposed by adding a power integral technique and utilizing sign function. To fulfill the requirement of asymmetric output constraints, an asymmetric barrier Lyapunov function (BLF) is constructed, which is different from tan-type and log-type BLFs. Based on the contradictory idea and finite-time stability theory, it is proved that there is no Zeno phenomenon under this event-trigger mechanism and all state variables of the closed-loop system attenuate to the origin in the finite-time while the output signals never violate the constraint. Furthermore, the result in this article is expanded to fixed-time control. Finally, a simulation example is given to demonstrate the effectiveness of the presented strategy.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Finite-Dimensional Observer-Based PI Regulation Control of a
           Reaction–Diffusion Equation

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      Authors: Hugo Lhachemi;Christophe Prieur;
      Pages: 6143 - 6150
      Abstract: This article investigates the output feedback setpoint regulation control of a reaction–diffusion equation by means of boundary control. The considered reaction–diffusion plant may be open-loop unstable. The proposed control strategy consists of the coupling of a finite-dimensional observer and a PI controller in order to achieve the boundary setpoint regulation control of various system outputs such as the Dirichlet and Neumann traces. In this context, it is shown that the order of the finite-dimensional observer can always be selected large enough, with an explicit criterion, to achieve both the stabilization of the plant and the setpoint regulation of the system output.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Time-Varying Quadratic-Programming-Based Error Redefinition Neural Network
           Control and Its Application to Mobile Redundant Manipulators

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      Authors: Lunan Zheng;Zhijun Zhang;
      Pages: 6151 - 6158
      Abstract: By incorporating the redefined error monitor function into the network design, an error redefinition neural network (ERNN) is proposed to control mobile redundant manipulators to execute the tracking task in this article. The global asymptotic stability and the strong antidisturbance capability of the ERNN are proved theoretically. Furthermore, the ERNN can overcome the overshoot and constant disturbance. Meanwhile, the ERNN is input-to-state stable, while the bounded time-varying disturbance is considered as the control input.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Adaptive Prescribed-Time Control for a Class of Uncertain Nonlinear
           Systems

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      Authors: Changchun Hua;Pengju Ning;Kuo Li;
      Pages: 6159 - 6166
      Abstract: This article focuses on the problem of prescribed-time control for a class of uncertain nonlinear systems. First, a prescribed-time stability theorem is proposed by following the adaptive technology for the first time. Based on this theorem, a new state feedback control strategy is put forward by using the backstepping method for high-order nonlinear systems with unknown parameters to ensure the prescribed-time convergence. Moreover, the prescribed-time controller is obtained in the form of continuous time-varying feedback, which can render all system states converge to zero within the prescribed time. It should be noted that the prescribed time is independent of system initial conditions, which means that the prescribed time can be set arbitrarily within the physical limitations. Finally, two simulation examples are provided to illustrate the effectiveness of our proposed algorithm.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Robust Static Output-Feedback Control of Stochastic Continuous
           Time-Delayed Systems

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      Authors: Eli Gershon;Uri Shaked;
      Pages: 6167 - 6172
      Abstract: In this article, a descriptor method is introduced for designing static output-feedback controllers for linear, continuous-time, retarded, stochastic systems that achieves a prescribed $H_{infty } {kern2.84526pt}$performance. A design solution is obtained for the uncertain case, where the parameters of the system matrices reside in a given polytope. The latter solution enables the derivation of the required constant output gain by solving a set of linear matrix inequalities that correspond to the vertices of the uncertainty polytope. The theory developed is also extended to the gain-scheduling case, and it is demonstrated by two examples. The first example compares various solution methods and the second is one of robust pitch control of an aircraft.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Adaptive Tracking and Stabilization of Nonholonomic Mobile Robots With
           Input Saturation

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      Authors: Jia-Wang Li;
      Pages: 6173 - 6179
      Abstract: This article investigates the control problems of tracking and stabilization simultaneously for nonholonomic mobile robots subjected to input constraints and parameter uncertainties. A saturated time-varying controller is developed by applying a novel error state modification with bounded auxiliary variables. To improve the estimation performance of unknown kinematic and dynamic parameters, two projection-type adaptation laws are presented, while radial basis function approximations are used to estimate uncertain dynamics. Simulations are conducted to verify the effectiveness of the proposed controller.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Novel Fixed-Time Protocol for First-Order Consensus Tracking With
           Disturbance Rejection

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      Authors: Yong Xu;Zhaozhan Yao;Renquan Lu;Bijoy K. Ghosh;
      Pages: 6180 - 6186
      Abstract: This technical note studies fixed-time consensus tracking with disturbance rejection for first-order multiagent systems. The communication topology among the leader and followers contains a directed spanning tree. The control input to the leader is time-varying and unknown to the followers, except that its upper bound is known a priori. A novel fixed-time protocol is devised based on discontinuous and nonlinear control. A fixed-time stability analysis for consensus tracking with disturbance rejection is completed as a one-step control process using nonsmooth analysis. An upper bound estimate for the settling time, independent of the initial conditions, is aesthetically pleasing, in comparison to previous results derived based on two-step control design technique using sliding modes. Finally, a numeric example confirms the theoretical results.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Fully Heterogeneous Containment Control of a Network of
           Leader–Follower Systems

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      Authors: Majid Mazouchi;Farzaneh Tatari;Bahare Kiumarsi;Hamidreza Modares;
      Pages: 6187 - 6194
      Abstract: This article develops a distributed solution to the fully heterogeneous containment control problem (CCP), for which not only the followers’ dynamics but also the leaders’ dynamics are nonidentical. A novel formulation of the fully heterogeneous CCP is first presented in which each follower constructs its virtual exosystem. To build these virtual exosystems by followers, a novel distributed algorithm is developed to calculate the so-called normalized level of influences (NLIs) of all leaders on each follower, and a novel adaptive distributed observer is designed to estimate the dynamics and states of all leaders that have an influence on each follower. Then, a distributed control protocol is proposed based on the cooperative output regulation framework, utilizing this virtual exosystem. Based on the estimations of leaders’ dynamics and states and NLIs of leaders on each follower, the solutions of the so-called linear regulator equations are calculated in a distributed manner, and consequently, a distributed control protocol is designed for solving the output containment problem. Finally, theoretical results are verified by performing numerical simulations.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Distributed Nash Equilibrium Seeking for Games in Second-Order Systems
           Without Velocity Measurement

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      Authors: Maojiao Ye;Jizhao Yin;Le Yin;
      Pages: 6195 - 6202
      Abstract: The design of distributed Nash equilibrium-seeking strategies for games in which the involved players are of second-order integrator-type dynamics is investigated in this article. Noticing that velocity signals are usually noisy or not available for feedback control in practical engineering systems, this article supposes that the velocity signals are not accessible for the players. To deal with the absence of velocity measurements, two estimators are designed. The first estimator is established by employing an observer, which has the same order as the players’ dynamics, to estimate the unavailable system states (e.g., the players’ velocities). The second estimator is designed based on a high-pass filter and is motivated by the incentive to reduce the order of the estimator, which in turn saves the computation costs of the seeking algorithms. On the basis of the designed observers/filters, distributed Nash equilibrium-seeking strategies are then established through incorporating them with consensus and gradient algorithms. It is analytically proven that the players’ actions can be regulated to the Nash equilibrium point and their velocities can be regulated to zero by utilizing the proposed velocity-free Nash equilibrium-seeking strategies. A numerical example is provided for the verification of the proposed algorithms.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Sliding Mode Control for Linear Impulsive Systems With Matched
           Disturbances

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      Authors: Xiaodi Li;Yongshun Zhao;
      Pages: 6203 - 6210
      Abstract: This article develops the sliding mode control (SMC) strategy for linear impulsive systems with matched disturbances. Such systems describe dynamical systems that evolve according to continuous process most of the time with matched disturbances, but instantaneously exhibit discontinuities, i.e., impulsive disturbances. A suitable sliding surface function is proposed and the resulting sliding mode dynamics are a class of linear impulsive systems. Some sufficient conditions coupled with impulse time sequences are proposed to guarantee the reachability of the predesigned sliding surface and the stability of the reduced-order impulsive systems under sliding motion, respectively. We show how restrictions on the structure of the systems and impulses should be imposed to ensure the feasibility of the proposed SMC strategy in comparison with general SMC in continuous space. To show the effectiveness of the proposed approach, two simulation examples are presented at the end.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • On the Role of Interconnection Directionality in the Quadratic Performance
           of Double-Integrator Networks

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      Authors: Hasan Giray Oral;Enrique Mallada;Dennice Gayme;
      Pages: 6211 - 6218
      Abstract: This article provides a quantitative and qualitative evaluation of the role of interconnection directionality in a general class of quadratic performance metrics for double-integrator networks. We first develop an analysis framework that can be used to evaluate the quadratic performance metrics of networks defined over a general class of directed graphs. A comparison between systems whose directed graph Laplacians are normal and their undirected counterparts unveils an interplay between the interconnection directionality and the control strategy that determines network performance. We show that directionality can significantly degrade performance; however, well-designed feedback can exploit directionality to mitigate this degradation or even improve performance.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Fast Desynchronization Algorithms for Decentralized Medium Access Control
           Based on Iterative Linear Equation Solvers

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      Authors: Daniel Silvestre;Joao Hespanha;Carlos Silvestre;
      Pages: 6219 - 6226
      Abstract: We tackle the problem of having multiple transmitters cooperating to be desynchronized using a distributed algorithm. Although this problem can also be found in surveillance, it has the most impact in achieving a fair access to a wireless shared communication medium at the medium access control layer in the context of wireless sensor networks. In this article, we first theoretically investigate the convergence rate of various optimization algorithms, giving closed-form expressions for the parameters achieving the best worst-case convergence rate. We then show that a recently proposed time-varying parameters Nesterov algorithm applied to this problem has worse performance assuming one can determine the number of sensors in the network. In order to remove such an assumption, the problem is seen as the solution of a linear equation corresponding to the first optimality condition. Both theoretically and in simulation, we show that using the Gauss–Seidel method improves the speed of convergence, although its performance degrades for large network sizes. In simulations, it is shown the behavior for various number of wireless devices, emphasizing how the algorithms actually perform in comparison with their worst-case theoretical rates for different network sizes.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • An Informativity Approach to the Data-Driven Algebraic Regulator Problem

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      Authors: Harry L. Trentelman;Henk J. van Waarde;M. Kanat Camlibel;
      Pages: 6227 - 6233
      Abstract: In this article, the classical algebraic regulator problem is studied in a data-driven context. The endosystem is assumed to be an unknown system that is interconnected to a known exosystem that generates disturbances and reference signals. The problem is to design a regulator so that the output of the (unknown) endosystem tracks the reference signal, regardless of its initial state and the incoming disturbances. In order to do this, we assume that we have a set of input-state data on a finite time-interval. We introduce the notion of data informativity for regulator design, and establish necessary and sufficient conditions for a given set of data to be informative. Also, formulas for suitable regulators are given in terms of the data. Our results are illustrated by means of two extended examples.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Robust Stability Analysis of Linear Parameter-Varying Systems With Markov
           Jumps

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      Authors: Alessandro N. Vargas;Cristiano M. Agulhari;Ricardo C. L. F. Oliveira;Victor M. Preciado;
      Pages: 6234 - 6239
      Abstract: This article presents conditions to assure the mean-square stability of linear parameter-varying systems with Markov jumps. The model dynamics are driven not only by a Markov chain but also by time-varying parameters that take values in a polytopic set. No assumption is imposed on how the parameters vary within the polytopic set, i.e., the variation rate can be arbitrarily fast. The proposed conditions stem from a homogeneous polynomial Lyapunov function in the state space, adapted to account for Markov jumps. The stability certificate is sought through linear matrix inequalities. Numerical examples illustrate this article’s contribution.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Quotients of Probabilistic Boolean Networks

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      Authors: Rui Li;Qi Zhang;Tianguang Chu;
      Pages: 6240 - 6247
      Abstract: A probabilistic Boolean network (PBN) is a discrete-time system composed of a collection of Boolean networks between which the PBN switches in a stochastic manner. This article focuses on the study of quotients of PBNs. Given a PBN and an equivalence relation on its state set, we consider a probabilistic transition system that is generated by the PBN; the resulting quotient transition system then automatically captures the quotient behavior of this PBN. We therefore describe a method for obtaining a probabilistic Boolean system that generates the transitions of the quotient transition system. Applications of this quotient description are discussed, and it is shown that for PBNs, controller synthesis can be performed easily by first controlling a quotient system and then lifting the control law back to the original network. A biological example is given to show the usefulness of the developed results.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Observability Criteria for Boolean Networks

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      Authors: Yongyuan Yu;Min Meng;Jun-e Feng;Ge Chen;
      Pages: 6248 - 6254
      Abstract: This article investigates observability of Boolean control networks (BCNs) and probabilistic Boolean networks (PBNs). First, weak observability of BCNs is discussed via the nonaugmented approach. The obtained result is then applied to determine (asymptotic) observability of PBNs. Finally, complexity of algorithms based on new criteria is analyzed. Compared with existing ones, time and space complexity do not get worse, even are improved under some mild conditions.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Consensusability Margin Optimization for Second-Order Multiagent Systems
           With Communication Uncertainties

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      Authors: Lina Rong;
      Pages: 6255 - 6262
      Abstract: In this article, the $mathcal {H}_{infty }$ optimization approach is used to study the consensusability margin optimization problems for distributed second-order sampled-data multiagent systems with communication uncertainties. The considered uncertainties are frequency-dependent and bounded in $mathcal {H}_{infty }$ norms. Specifically, for both the state-based protocols with relative damping and absolute damping, this article attempts to answer two questions: 1) how to characterize the control parameters for achieving robust consensus; and 2) what is the maximal consensusability margin and how to find, if one exists, the parameter to achieve this optimal performance. It is shown that the consensusability margin optimization problems are constraint optimization problems, which are to be specified by specific problem parameters and can be discussed by designing the network complementary sensitivity function matrices of the closed-loop multiagent systems. Moreover, it is shown that the infimums of the $mathcal {H}_{infty }$ norms of the network complementary sensitivity function matrices under both protocols are independent of network topologies.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Distributed Model Predictive Control With Reconfigurable Terminal
           Ingredients for Reference Tracking

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      Authors: Ahmed Aboudonia;Annika Eichler;Francesco Cordiano;Goran Banjac;John Lygeros;
      Pages: 6263 - 6270
      Abstract: Various efforts have been devoted to developing stabilizing distributed model predictive control (MPC) schemes for tracking piecewise constant references. In these schemes, terminal sets are usually computed offline and used in the MPC online phase to guarantee recursive feasibility and asymptotic stability. Maximal invariant terminal sets do not necessarily respect the distributed structure of the network, hindering the distributed implementation of the controller. On the other hand, ellipsoidal terminal sets respect the distributed structure, but may lead to conservative schemes. In this article, a novel distributed MPC scheme is proposed for reference tracking of networked dynamical systems, where the terminal ingredients are reconfigured online depending on the closed-loop states to alleviate the aforementioned issues. The resulting nonconvex infinite-dimensional problem is approximated using a quadratic program. The proposed scheme is tested in simulation, where the proposed MPC problem is solved using distributed optimization.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Lyapunov Approach to Robust Cooperative Output Regulation of Multiagent
           Systems Under Infinite Communication Delays

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      Authors: Qianghui Zhou;Xiang Xu;Lu Liu;Gang Feng;
      Pages: 6271 - 6278
      Abstract: This article investigates the robust cooperative output regulation problem of heterogeneous uncertain linear multiagent systems with switching topologies and infinite distributed communication delays. A novel distributed observer is proposed for each agent to estimate the state of the so-called exosystem by taking consideration of both switching topologies and infinite distributed communication delays. A distributed output feedback controller is then developed based on the internal model principle and the estimated state without using the prior knowledge of communication delays. It is shown via the newly developed Lyapunov-like method that the robust cooperative output regulation problem can be solved under some mild assumptions. Finally, a numerical example is given to demonstrate the effectiveness of the proposed controller.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Regulation of Markov Jump Linear Systems Subject to Polytopic
           Uncertainties

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      Authors: José Nuno A. D. Bueno;Lucas B. Marcos;Kaio D. T. Rocha;Marco H. Terra;
      Pages: 6279 - 6286
      Abstract: When discrete-time Markov jump linear systems are prone to the damaging effects of polytopic uncertainties, it is necessary to address all the vertices of each Markov mode in order to properly design robust controllers. To this end, we propose a robust recursive linear–quadratic regulator for this class of systems. We define a quadratic min–max optimization problem by combining least-squares and penalty functions in a unified framework. We design a one-step cost function to encompass the entire set of vertices of each mode altogether, while maintaining its quadratic structure and the convexity of the problem. The solution is then obtained recursively and does not require numerical optimization packages. We establish conditions for convergence and stability by extending the matrix structure of the recursive solution. In addition, we provide numerical and real-world application examples to validate our method and to emphasize recursiveness and diminished computational effort.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Optimal Transport for a Class of Linear Quadratic Differential Games

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      Authors: Daniel Owusu Adu;Tamer Başar;Bahman Gharesifard;
      Pages: 6287 - 6294
      Abstract: We consider a setting where two noncooperative players optimally influence the evolution of an initial spatial probability in a game-theoretic hierarchical fashion (Stackelberg differential game), so that at a specific final time the distribution of the state matches a given final target measure. We provide a sufficient condition for the existence and uniqueness of an optimal transport map and prove that it can be characterized as the gradient of some convex function. An important by-product of our formulation is that it provides a means to study a class of Stackelberg differential games where the initial and final states of the underlying system are uncertain, but drawn randomly from some probability measures.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • A Reconnaissance Penetration Game With Territorial-Constrained Defender

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      Authors: Li Liang;Fang Deng;Jianan Wang;Maobin Lu;Jie Chen;
      Pages: 6295 - 6302
      Abstract: A reconnaissance penetration game is a classic target-attacker-defender game. In this game, a reconnaissance UAV (namely attacker) tries to avoid the defender and reconnoiter a target as close as possible, whereas a target tries to escape the attacker with the help of defender. Practically, the defender is considered constrained in a certain territory to capture the attacker and help the target. This article is primarily concerned with the winning region for three players. An explicit policy method is proposed to construct the barrier analytically. In addition, taking practical payoff functions into account, a complete solution to the reconnaissance game is provided by fusing the games of kind and degree. Simulation results are elaborated to showcase the effectiveness of the proposed policy.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Decentralized Cohesive Response During Transitions for Higher-Order Agents
           Under Network Delays

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      Authors: Anuj Tiwari;Santosh Devasia;
      Pages: 6303 - 6309
      Abstract: Cohesion in networks during transitions from one consensus value to another, i.e., the ability of agents to respond in a similar manner during the transition, can be as important as achieving the new consensus value. Existing decentralized network control strategies mainly concern with the convergence speed to the final consensus value. However, even with increased convergence speed, the level of cohesion loss during transitions can be large. This loss of cohesion during transition (and tracking of varying consensus values) can be alleviated using a recently developed delayed self reinforcement (DSR) approach. However, the current DSR-based approach assumes ideal conditions with agents having instant access to neighbor information—without network delays arising during sensing or communication between neighbors, as well as computation of control actions of each agent, which can cause instability. The main contributions of this article are to use the Rouchè’s theorem to 1) prove the stability of the DSR approach if the network delay is not too large; and 2) compute an estimate of the acceptable network delay margin (DM) for stability. Additionally, a simulation example is used to illustrate the estimation approach for network DMs with DSR, and show that cohesion is maintained with DSR even with network delays when compared to the case without DSR.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Distributed Antiwindup Consensus Control of Heterogeneous Multiagent
           Systems Over Markovian Randomly Switching Topologies

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      Authors: Jingyao Wang;Guanghui Wen;Zhisheng Duan;
      Pages: 6310 - 6317
      Abstract: The consensus control of multiagent systems (MASs) over randomly switching communication topologies has drawn increasing attention from researchers, since the mean square consensus or the most surely consensus is significant and practical. This manuscript focuses on the output consensus problem for heterogeneous MASs with input saturation constraints over the Markovian randomly switching topologies. The main challenge of solving the concerned problem lies in the interplay among the heterogeneous dynamics, input saturation constraints and the Markovian randomly switching topologies. To overcome such a challenge, a class of distributed adaptive observers is first designed for all agents to deal with the uncertainty caused by the randomly switching topologies. Then, a class of local state observers is presented for estimating each agent’s state information. Based on the above steps, a class of antiwindup controllers is constructed and the control gain matrices are selected using only the dynamics information of each node. Finally, the effectiveness of the consensus protocol is demonstrated.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • TechRxiv: Share Your Preprint Research with the World!

    • Free pre-print version: Loading...

      Pages: 6318 - 6318
      Abstract: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Introducing IEEE Collabratec

    • Free pre-print version: Loading...

      Pages: 6319 - 6319
      Abstract: Advertisement.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
  • Expand Your Network, Get Rewarded

    • Free pre-print version: Loading...

      Pages: 6320 - 6320
      Abstract: Advertisement.
      PubDate: Nov. 2022
      Issue No: Vol. 67, No. 11 (2022)
       
 
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