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COMPUTER SCIENCE (1188 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 19)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 24)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 9)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 13)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 16)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 6)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 15)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 6)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 3)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 21)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 9)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 27)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 28)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 16)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 6)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 18)
Advances in Computer Science : an International Journal     Open Access   (Followers: 15)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 54)
Advances in Engineering Software     Hybrid Journal   (Followers: 27)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 13)
Advances in Human-Computer Interaction     Open Access   (Followers: 21)
Advances in Materials Sciences     Open Access   (Followers: 16)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 43)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 5)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 7)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal  
Air, Soil & Water Research     Open Access   (Followers: 10)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 5)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 11)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 13)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Clinical Informatics     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 10)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 15)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 143)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 7)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 4)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 11)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Big Data and Cognitive Computing     Open Access   (Followers: 2)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 291)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 19)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 35)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 46)
British Journal of Educational Technology     Hybrid Journal   (Followers: 150)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 20)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 2)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 56)
Communications of the Association for Information Systems     Open Access   (Followers: 18)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 9)
Computación y Sistemas     Open Access  
Computation     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 11)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 15)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 30)
Computer     Full-text available via subscription   (Followers: 94)
Computer Aided Surgery     Hybrid Journal   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 10)
Computer Engineering and Applications Journal     Open Access   (Followers: 5)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 23)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)
Computer Music Journal     Hybrid Journal   (Followers: 18)
Computer Physics Communications     Hybrid Journal   (Followers: 6)

        1 2 3 4 5 6 | Last

Journal Cover Automatica
  [SJR: 4.315]   [H-I: 188]   [11 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 0005-1098
   Published by Elsevier Homepage  [3177 journals]
  • Iterative learning impedance control for rehabilitation robots driven by
           series elastic actuators
    • Authors: Xiang Li; Yun-Hui Liu; Haoyong Yu
      Pages: 1 - 7
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Xiang Li, Yun-Hui Liu, Haoyong Yu
      Existing control techniques for rehabilitation robots commonly ignore robot dynamics by assuming a perfect inner control loop or are limited to rigid-joint robots. The dynamic stability of compliantly-actuated rehabilitation robots, consisting of the dynamics of both robot and compliant actuator, is not theoretically grounded. This paper presents an iterative learning impedance controller for rehabilitation robots driven by series elastic actuators (SEAs), where the control objective is specified as a desired impedance model. The desired impedance model is achieved in an iterative manner, which suits the repeating nature of patients’ task through therapeutic process and also guarantees the transient performance of robot. The stability of the overall system is rigorously proved with Lyapunov methods by taking into account both the robot and actuator dynamics. Experimental results are presented to illustrate the performance of the proposed iterative control scheme.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.031
      Issue No: Vol. 90 (2018)
  • Uniform convergence for signed networks under directed switching
    • Authors: Deyuan Meng; Ziyang Meng; Yiguang Hong
      Pages: 8 - 15
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Deyuan Meng, Ziyang Meng, Yiguang Hong
      This paper contributes to developing necessary convergence conditions for directed signed networks subject to cooperative and antagonistic interactions. A class of Laplacian-dependent convergence conditions is presented in the presence of switching topologies. It is shown that the switching signed networks converge monotonically to the intersection space of the null spaces of all Laplacian matrices. Furthermore, the uniform bipartite consensus (respectively, uniform asymptotic stability) of switching signed networks is tied closely to the simultaneous structural balance (respectively, unbalance) of the switching signed digraphs associated with them.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.028
      Issue No: Vol. 90 (2018)
  • Design of measurement difference autocovariance method for estimation of
           process and measurement noise covariances
    • Authors: Jindřich Duník; Oliver Kost; Ondřej Straka
      Pages: 16 - 24
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Jindřich Duník, Oliver Kost, Ondřej Straka
      The paper deals with the estimation of the process and measurement noise covariance matrices of a system described by the linear time-varying state–space model. In particular, the stress is laid on the correlation methods and a novel method, the measurement difference autocovariance method, is designed. The proposed method is based on the statistical analysis of an augmented measurement prediction error leading to a system of linear matrix equations for the elements of the noise covariance matrices. Compared to other correlation methods, the proposed method provides unbiased estimates even for a finite number of measurements. The theoretical results are discussed and illustrated in a numerical example.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.040
      Issue No: Vol. 90 (2018)
  • Set-membership errors-in-variables identification of MIMO linear systems
    • Authors: Vito Cerone; Valentino Razza; Diego Regruto
      Pages: 25 - 37
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Vito Cerone, Valentino Razza, Diego Regruto
      In this paper, we consider the problem of set-membership identification of multiple-input multiple-output (MIMO) linear models when both input and output measurements are affected by bounded additive noise. Firstly, we propose a general formulation that allows the user to take into account possible a-priori information on the structure of the MIMO model to be identified. Then, we formulate the problem in terms of a suitable polynomial optimization problem that is solved by means of a convex relaxation approach. To show the effectiveness of the proposed approach, we test the original MIMO identification algorithm on a simulation example, as well as on a set of input–output experimental data, collected on a multiple-input multiple-output electronic process simulator.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.042
      Issue No: Vol. 90 (2018)
  • A hierarchical multi-rate MPC scheme for interconnected systems
    • Authors: Marcello Farina; Xinglong Zhang; Riccardo Scattolini
      Pages: 38 - 46
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Marcello Farina, Xinglong Zhang, Riccardo Scattolini
      This paper presents a hierarchical control scheme for interconnected linear systems. At the higher layer, a robust centralized Model Predictive Control (MPC) algorithm based on a reduced order dynamic model of the overall system optimizes a long-term performance index penalizing the deviation of the state and the control input from their nominal values. At the lower layer, local MPC regulators, possibly working at different rates, are designed for the full order models of the subsystems to refine the control action computed at the higher layer. A simulation experiment is presented to describe the implementation aspects and the potentialities of the proposed approach.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.036
      Issue No: Vol. 90 (2018)
  • Optimal filtering for a class of linear Itô stochastic systems: The
           dichotomic case
    • Authors: Vasile Dragan; Samir Aberkane; Ioan-Lucian Popa
      Pages: 47 - 53
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Vasile Dragan, Samir Aberkane, Ioan-Lucian Popa
      This paper focuses on the problem of optimal H 2 filtering for a class of continuous-time stochastic systems without assuming their exponential stability in the mean square sense. Indeed, the stability assumption is relaxed and we assume instead that the Lyapunov operator associated to the dynamical stochastic system is exponentially dichotomic. The optimal solution of the considered optimization problem is expressed in terms of the unique solution of a suitable algebraic Lyapunov equation and the stabilizing solution of a certain algebraic Riccati equation.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.025
      Issue No: Vol. 90 (2018)
  • Identification of structured state-space models
    • Authors: Chengpu Yu; Lennart Ljung; Michel Verhaegen
      Pages: 54 - 61
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Chengpu Yu, Lennart Ljung, Michel Verhaegen
      Identification of structured state-space (gray-box) model is popular for modeling physical and network systems. Due to the non-convex nature of the gray-box identification problem, good initial parameter estimates are crucial for successful applications. In this paper, the non-convex gray-box identification problem is reformulated as a structured low-rank matrix factorization problem by exploiting the rank and structured properties of a block Hankel matrix constructed by the system impulse response. To address the low-rank optimization problem, it is first transformed into a difference-of-convex (DC) formulation and then solved using the sequentially convex relaxation method. Compared with the classical gray-box identification methods like the prediction-error method (PEM), the new approach turns out to be more robust against converging to non-global minima, as supported by a simulation study. The developed identification can either be directly used for gray-box identification or provide an initial parameter estimate for the PEM.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.023
      Issue No: Vol. 90 (2018)
  • Stability analysis of DC microgrids with constant power load under
           distributed control methods
    • Authors: Zhangjie Liu; Mei Su; Yao Sun; Hua Han; Xiaochao Hou; Josep M. Guerrero
      Pages: 62 - 72
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Zhangjie Liu, Mei Su, Yao Sun, Hua Han, Xiaochao Hou, Josep M. Guerrero
      Constant power loads (CPLs) often cause instability due to its negative impedance characteristics. In this study, the stability of a DC microgrid with CPLs under a distributed control that aims at current sharing and voltage recovery is analyzed. The effect of the negative impedance on the behavior of distributed controller is investigated. The small-signal model is established to predict the system qualitative behavior around equilibrium. The stability conditions of the system with time delay are derived based on the equivalent linearized model. Additionally, eigenvalue analysis based on inertia theorem provides analytical sufficient conditions as a function of the system parameters, and thus it leads to a design guideline to build reliable microgrids. Simulations are performed to confirm the effectiveness and validity of the proposed method.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.051
      Issue No: Vol. 90 (2018)
  • Enlarging the basin of attraction by a uniting output feedback controller
    • Authors: Miguel A. Davó; Christophe Prieur; Mirko Fiacchini; Dragan Nešić
      Pages: 73 - 80
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Miguel A. Davó, Christophe Prieur, Mirko Fiacchini, Dragan Nešić
      We consider a system for which two predesigned stabilizing output feedback controllers with bounded domains of attraction are known. One renders the system asymptotically stable with some desired performance, and the other provides ultimate boundedness with larger domain of attraction. Assuming that two subsets of the domains of attraction are known, one larger than the other, this work states the problem of combining both controllers with the goal of guaranteeing asymptotic stability properties in the largest subset while the desired performance is locally achieved. We design a switching logic between the controllers that solves the problem, based on the existence of a local tunable observer. The resulting control law is defined by a hybrid output feedback controller. The effectiveness of the proposed solution is illustrated by a numerical example.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.044
      Issue No: Vol. 90 (2018)
  • On stability and convergence of optimal estimation for networked control
           systems with dual packet losses without acknowledgment
    • Authors: Hong Lin; Hongye Su; Michael Z.Q. Chen; Zhan Shu; Renquan Lu; Zheng-Guang Wu
      Pages: 81 - 90
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Hong Lin, Hongye Su, Michael Z.Q. Chen, Zhan Shu, Renquan Lu, Zheng-Guang Wu
      This paper studies the optimal state estimation problem for networked control systems with control and observation packet losses but without packet acknowledgment (ACK). The packet ACK is a signal sent by the actuator to inform the estimator whether control packets are lost or not. Systems with packet ACK are usually called transmission control protocol (TCP)-like systems, and those without ACK are named user datagram protocol (UDP)-like systems. For UDP-like systems, the optimal estimator is derived and it is consisted of an exponentially increasing number of terms. By developing an auxiliary estimator, it is shown that there exists a critical observation packet arrival rate determining the stability of the expected EC (EEC), and it is identical to its counterpart for TCP-like systems. It is revealed that whether there is packet ACK or not has no effect on the stability of the EEC. Furthermore, under some conditions the EEC converges exponentially.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.059
      Issue No: Vol. 90 (2018)
  • Stability analysis of Extended, Cubature and Unscented Kalman Filters for
           estimating stiff continuous–discrete stochastic systems
    • Authors: Gennady Yu. Kulikov; Maria V. Kulikova
      Pages: 91 - 97
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Gennady Yu. Kulikov, Maria V. Kulikova
      This paper studies stiffness and stability properties of Extended Cubature and Unscented Kalman Filters applied to continuous–discrete stochastic systems with stiff dynamic behavior. The main part of these methods relies on numerical integration of Moment Differential Equations (MDEs). Our focus is to understand how the stiffness of MDEs influences performance of the filters. The proposed linear stability analysis shows that the MDEs that havearisen within these methods can enlarge the stiffness of continuous-time stochastic model and, hence, require solvers with advanced stability properties for their effective and accurate treatment. Besides, the proposed nonlinear stability analysis proves that such MDEs may become extremely unstable in simulation intervals. The latter raises the uncertainty of state estimation and results in two interesting implications: (i) the lower-order Extended Kalman Filter outperforms the higher-order Cubature and Unscented Kalman Filters in the accuracy of state estimation of stochastic systems with unstable MDE behavior; (ii) the methods under exploration fail when the stiffness is large enough. Our theoretical consideration is supported by numerical tests with filters based on the MATLAB code ode15s, which is a benchmark solver for stiff ODEs. These are examined on linear and nonlinear stiff continuous-time stochastic models.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.055
      Issue No: Vol. 90 (2018)
  • Stability analysis of a general class of singularly perturbed linear
           hybrid systems
    • Authors: Jihene Ben Rejeb; Irinel-Constantin Morărescu; Antoine Girard; Jamal Daafouz
      Pages: 98 - 108
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Jihene Ben Rejeb, Irinel-Constantin Morărescu, Antoine Girard, Jamal Daafouz
      We introduce and analyze a general class of singularly perturbed linear hybrid systems with both switches and impulses, in which the slow or fast nature of the variables can be mode-dependent. This means that, at switching instants, some of the slow variables can become fast and vice-versa. Firstly, we show that using a mode-dependent variable reordering we can rewrite this class of systems in a form in which the variables preserve their slow or fast nature over time. Secondly, we establish, through singular perturbation techniques, an upper bound on the minimum dwell-time ensuring the overall system’s stability. Remarkably, this bound is the sum of two terms. The first term, which can be equal to zero, only depends on the matrices of the reduced order linear hybrid system describing the slow dynamics and corresponds to an upper bound on the minimum dwell time ensuring the stability of that system. The order of magnitude of the second term is determined by that of the parameter defining the ratio between the two time-scales of the singularly perturbed system. We show that the proposed framework can also take into account the change of dimension of the state vector at switching instants. Numerical illustrations complete our study.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.019
      Issue No: Vol. 90 (2018)
  • On kernel design for regularized LTI system identification
    • Authors: Tianshi Chen
      Pages: 109 - 122
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Tianshi Chen
      There are two key issues for the kernel-based regularization method: one is how to design a suitable kernel to embed in the kernel the prior knowledge of the LTI system to be identified, and the other one is how to tune the kernel such that the resulting regularized impulse response estimator can achieve a good bias–variance tradeoff. In this paper, we focus on the issue of kernel design. Depending on the type of the prior knowledge, we propose two methods to design kernels: one is from a machine learning perspective and the other one is from a system theory perspective. We also provide analysis results for both methods, which not only enhances our understanding for the existing kernels but also directs the design of new kernels.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.039
      Issue No: Vol. 90 (2018)
  • Simultaneous velocity consensus and shape control for a finite number of
           point agents on the unit circle
    • Authors: Christian Lageman; Uwe R. Helmke; Brian D.O. Anderson
      Pages: 123 - 129
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Christian Lageman, Uwe R. Helmke, Brian D.O. Anderson
      In this paper we study a second order, distributed control system for a finite number of point agents on the unit circle that achieves simultaneously velocity consensus and distance based formation shape control. Based on tools from Riemannian geometry, we propose a system of second order differential equations on the N -dimensional torus that achieves these two goals. We prove convergence of the trajectories to single closed geodesics on a torus and investigate the stability properties of the distributed algorithm.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.060
      Issue No: Vol. 90 (2018)
  • The generalized cross validation filter
    • Authors: Giulio Bottegal; Gianluigi Pillonetto
      Pages: 130 - 137
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Giulio Bottegal, Gianluigi Pillonetto
      Generalized cross validation (GCV) is one of the most important approaches used to estimate parameters in the context of inverse problems and regularization techniques. A notable example is the determination of the smoothness parameter in splines. When the data are generated by a state space model, like in the spline case, efficient algorithms are available to evaluate the GCV score with complexity that scales linearly in the data set size. However, these methods are not amenable to on-line applications since they rely on forward and backward recursions. Hence, if the objective has been evaluated at time t − 1 and new data arrive at time t , then O ( t ) operations are needed to update the GCV score. In this paper we instead show that the update cost is O ( 1 ) , thus paving the way to the on-line use of GCV. This result is obtained by deriving the novel GCV filter which extends the classical Kalman filter equations to efficiently propagate the GCV score over time. We also illustrate applications of the new filter in the context of state estimation and on-line regularized linear system identification.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.054
      Issue No: Vol. 90 (2018)
  • Yield trajectory tracking for hyperbolic age-structured population systems
    • Authors: Kevin Schmidt; Iasson Karafyllis; Miroslav Krstic
      Pages: 138 - 146
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Kevin Schmidt, Iasson Karafyllis, Miroslav Krstic
      For population systems modeled by age-structured hyperbolic partial differential equations (PDEs) that are bilinear in the input and evolve with a positive-valued infinite-dimensional state, global stabilization of constant yield set points was achieved in prior work. Seasonal demands in biotechnological production processes give rise to time-varying yield references. For the proposed control objective aiming at a global attractivity of desired yield trajectories, multiple non-standard features have to be considered: a non-local boundary condition, a PDE state restricted to the positive orthant of the function space and arbitrary restrictive but physically meaningful input constraints. Moreover, we provide Control Lyapunov Functionals ensuring an exponentially fast attraction of adequate reference trajectories. To achieve this goal, we make use of the relation between first-order hyperbolic PDEs and integral delay equations leading to a decoupling of the input-dependent dynamics and the infinite-dimensional internal one. Furthermore, the dynamic control structure does not necessitate exact knowledge of the model parameters or online measurements of the age-profile. With a Galerkin-based numerical simulation scheme using the key ideas of the Karhunen–Loève-decomposition, we demonstrate the controller’s performance.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.050
      Issue No: Vol. 90 (2018)
  • Development of a collision-avoidance vector based control algorithm for
           automated in-vivo transportation of biological cells
    • Authors: Xiaojian Li; Shuxun Chen; Chichi Liu; Shuk Han Cheng; Yong Wang; Dong Sun
      Pages: 147 - 156
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Xiaojian Li, Shuxun Chen, Chichi Liu, Shuk Han Cheng, Yong Wang, Dong Sun
      With the rapid development of precision medicine, the in-vivo manipulation of microparticles has attracted increased attention in recent years. Collision is a main cause of the failure of in-vivo particle transportation. In this paper, an automated control approach with obstacle avoidance function is proposed for in-vivo cell transportation. In the proposed approach, a collision-avoidance vector method is utilized to avoid obstacles during the transportation of the target cell. The proposed method integrates obstacle detection and collision avoidance into a single step, hence reducing the duration of online processing while enhancing the accuracy of obstacle detection. With the proposed approach, different collision avoidance strategies are designed to suit for different transportation environments. The proposed approach exhibits the advantages of reduced online calculation, fast response, high accuracy, and disturbance compensation. Experiments are performed to demonstrate the effectiveness of the proposed controller.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.022
      Issue No: Vol. 90 (2018)
  • Rigid-body attitude stabilization with attitude and angular rate
    • Authors: Qiang Shen; Chengfei Yue; Cher Hiang Goh; Baolin Wu; Danwei Wang
      Pages: 157 - 163
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Qiang Shen, Chengfei Yue, Cher Hiang Goh, Baolin Wu, Danwei Wang
      In this paper, a solution to the problem of rest-to-rest three-axis attitude reorientation of a fully actuated rigid body under multiple attitude-constraint zones and angular velocity limits is presented. Based on the unit-quaternion parameterized attitude-constrained zones, a quadratic potential function is developed with a global minimum locating at the desired attitude and high potential closing to the constrained zones. In addition, to limit the magnitude of the angular velocity, another logarithmic potential function is also designed. Using these two potential functions and sliding mode control technique, a nonlinear attitude control law is obtained to guarantee asymptotic convergence of the closed-loop system with consideration of attitude and angular rate constraints, and external disturbances. The effectiveness of the constrained attitude control method is demonstrated through numerical simulation.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.029
      Issue No: Vol. 90 (2018)
  • Arc Length based Maximal Lyapunov Functions and domains of attraction
           estimation for polynomial nonlinear systems
    • Authors: Mojtaba Zarei; Ahmad Kalhor; Dani Brake
      Pages: 164 - 171
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Mojtaba Zarei, Ahmad Kalhor, Dani Brake
      In the phase space of a dynamical system containing an asymptotically stable equilibrium point, the Arc Length Function (ALF) is defined as sum of length differential elements of phase trajectories starting from state points and ending at the equilibrium point. It is shown that receding from the origin and verging on the Domain of Attraction (DoA) boundary causes ALF to be increased drastically. According to the latter issue and regarding to other properties, it is shown that ALF is a Maximal Lyapunov Function. To this end, a numerical method to approximate the ALF as a polynomial function is proposed. To ensure that the approximated function has positive value and negative derivative inside the desired region, the homotopy continuation method is used. Thus, the approximated ALF presents an ensured Lyapunov behavior to estimate DoA. The efficacy of the proposed method is demonstrated by several simulation examples.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.056
      Issue No: Vol. 90 (2018)
  • Robust MPC for tracking constrained unicycle robots with additive
    • Authors: Zhongqi Sun; Li Dai; Kun Liu; Yuanqing Xia; Karl Henrik Johansson
      Pages: 172 - 184
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Zhongqi Sun, Li Dai, Kun Liu, Yuanqing Xia, Karl Henrik Johansson
      Two robust model predictive control (MPC) schemes are proposed for tracking unicycle robots with input constraint and bounded disturbances: tube-MPC and nominal robust MPC (NRMPC). In tube-MPC, the control signal consists of a control action and a nonlinear feedback law based on the deviation of the actual states from the states of a nominal system. It renders the actual trajectory within a tube centered along the optimal trajectory of the nominal system. Recursive feasibility and input-to-state stability are established and the constraints are ensured by tightening the input domain and the terminal region. In NRMPC, an optimal control sequence is obtained by solving an optimization problem based on the current state, and then the first portion of this sequence is applied to the real system in an open-loop manner during each sampling period. The state of the nominal system model is updated by the actual state at each step, which provides additional feedback. By introducing a robust state constraint and tightening the terminal region, recursive feasibility and input-to-state stability are guaranteed. Simulation results demonstrate the effectiveness of both strategies proposed.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.048
      Issue No: Vol. 90 (2018)
  • Optimal under-actuated kinematic motion planning on the ϵ-group
    • Authors: Helen Clare Henninger; James Douglas Biggs
      Pages: 185 - 195
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Helen Clare Henninger, James Douglas Biggs
      A global motion planning method is described based on the solution of minimum energy-type curves on the frame bundle of connected surfaces of arbitrary constant cross sectional curvature ϵ . Applying the geometric framing of Pontryagin’s principle gives rise to necessary conditions for optimality in the form of a boundary value problem. This arbitrary dimensional boundary value problem is solved using a numerical shooting method derived from a general Lax pair solution. The paper then specializes to the 3-dimensional case where the Lax pair equations are integrable. A semi-analytic method for matching the boundary conditions is proposed by using the analytic form of the extremal solutions and a closed form solution for the exponential map. This semi-analytical approach has the advantage that an analytic description of the control accelerations can be derived and enables actuator constraints to be incorporated via time reparametrization. The method is applied to two examples in space mechanics: the attitude control of a spacecraft with two reaction wheels and the spacecraft docking problem.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.049
      Issue No: Vol. 90 (2018)
  • Optimal distributed stochastic mirror descent for strongly convex
    • Authors: Deming Yuan; Yiguang Hong; Daniel W.C. Ho; Guoping Jiang
      Pages: 196 - 203
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Deming Yuan, Yiguang Hong, Daniel W.C. Ho, Guoping Jiang
      In this paper we consider convergence rate problems for stochastic strongly-convex optimization in the non-Euclidean sense with a constraint set over a time-varying multi-agent network. We propose two efficient non-Euclidean stochastic subgradient descent algorithms based on the Bregman divergence as distance-measuring function rather than the Euclidean distances that were employed by the standard distributed stochastic projected subgradient algorithms. For distributed optimization of non-smooth and strongly convex functions whose only stochastic subgradients are available, the first algorithm recovers the best previous known rate of O ( ln ( T ) ∕ T ) (where T is the total number of iterations). The second algorithm is an epoch variant of the first algorithm that attains the optimal convergence rate of O ( 1 ∕ T ) , matching that of the best previously known centralized stochastic subgradient algorithm. Finally, we report some simulation results to illustrate the proposed algorithms.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.053
      Issue No: Vol. 90 (2018)
  • Consensus in opinion dynamics as a repeated game
    • Authors: Dario Bauso; Mark Cannon
      Pages: 204 - 211
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Dario Bauso, Mark Cannon
      We study an n -agent averaging process with dynamics subject to controls and adversarial disturbances. The model arises in multi-population opinion dynamics with macroscopic and microscopic intertwined dynamics. The averaging process describes the influence from neighbouring populations, whereas the input term indicates how the distribution of opinions in the population changes as a result of dynamical evolutions at a microscopic level (individuals’ changing opinions). The input term is obtained as the vector payoff of a two player repeated game. We study conditions under which the agents achieve robust consensus to some predefined target set. Such conditions build upon the approachability principle in repeated games with vector payoffs.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.062
      Issue No: Vol. 90 (2018)
  • A family of piecewise affine control Lyapunov functions
    • Authors: Ngoc Anh Nguyen; Sorin Olaru
      Pages: 212 - 219
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Ngoc Anh Nguyen, Sorin Olaru
      This paper presents a novel method to construct a family of piecewise affine control Lyapunov functions. Unlike most of existing methods which require the contractivity of their domain of definition, the proposed control Lyapunov functions are defined over a so-called N -step controllable set, which is known not to be contractive. Accordingly, a robust control design procedure is presented which only requires solving a linear programming problem at each sampling time. The construction is finally illustrated via a numerical example.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.052
      Issue No: Vol. 90 (2018)
  • Design of adaptive output feedback synchronizing controllers for networked
           PDEs with boundary and in-domain structured perturbations and disturbances
    • Authors: Michael A. Demetriou
      Pages: 220 - 229
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Michael A. Demetriou
      This work considers a class of networked distributed parameter systems with structured perturbations and disturbances. These systems are assumed to have identical unknown structured perturbations and unknown disturbances but different initial conditions. The multi-task controllers aim to adaptively compensate both structured perturbation and disturbance effects. Additionally, to follow a virtual leader by ensuring the asymptotic convergence of each of the networked states to the leader’s state. Finally, to synchronize in the sense of the convergence of the pairwise state errors. A four-part controller is proposed to address all tasks and provides many new elements for control of networked spatially distributed systems. The adaptive estimates of both the disturbance and the structured perturbation terms include a consensus term in their adaptive laws which provide the first coupling of the networked systems and aims at providing a weak version of persistence of excitation. The consensus protocol included in the synchronization component of the controller addresses the communication burden by transmitting output signals to its communicating systems instead of entire states and further, adapts the synchronization weights in proportion to the pairwise state disagreement, as a means to minimize the control effort. An abstract theoretical framework is established which handles a wide class of infinite dimensional systems including PDEs with both in-domain and boundary control and observation, and is conducive to well-posedness and stability analysis. Using the proposed multi-component controllers, the convergence of the networked states to the leader’s state is established using Lyapunov stability arguments for infinite dimensional systems, along with the boundedness of all signals. The well-posedness of all networked closed loop systems is shown by using established results on an analytic semigroup approach. A numerical example involving five networked partial differential equations with boundary observation, control, and disturbances and structured perturbations at the boundary, is presented and which provides insights on the control and synchronization of networked PDE systems.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.047
      Issue No: Vol. 90 (2018)
  • Interval estimation for continuous-time switched linear systems
    • Authors: Haifa Ethabet; Djahid Rabehi; Denis Efimov; Tarek Raïssi
      Pages: 230 - 238
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Haifa Ethabet, Djahid Rabehi, Denis Efimov, Tarek Raïssi
      This paper deals with the design of interval observers for switched linear systems (SLS), a class of hybrid systems. Under the assumption that the disturbances and the measurement noise are bounded, upper and lower bounds for the state are calculated. New conditions of cooperativity in discrete-time instants are firstly proposed. Then, some techniques for interval estimation are developed in continuous-time. It is shown that it is possible to calculate the observer gains making the estimation error dynamics cooperative and stable via some change of coordinates under arbitrary switching sequences. The performances of the developed techniques are illustrated through numerical examples.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.035
      Issue No: Vol. 90 (2018)
  • Adaptive observer design for a class of nonlinear systems. Application to
           speed sensorless induction motor
    • Authors: Mondher Farza; Mohammed M’Saad; Tomas Ménard; Ali Ltaief; Tarak Maatoug
      Pages: 239 - 247
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Mondher Farza, Mohammed M’Saad, Tomas Ménard, Ali Ltaief, Tarak Maatoug
      This paper investigates the problem of designing an adaptive high gain observer for a class of MIMO non uniformly observable systems involving some unknown constant parameters. The considered systems are not necessarily linear with respect to the unknown parameters up to a well defined parameter structure involving the parameter characteristic indices. The observer design model is elaborated from the state system dynamics augmented with the dynamics of the unknown parameters. An adaptive observer whose gain is derived from the resolution of a Lyapunov differential equation is proposed and its exponential convergence is established under an appropriate persistent excitation property up to the classical high gain state observer design assumptions. Moreover, it is shown that the equations of the observer can be put under an adaptive form emphasizing thereby its versatility to include several available adaptive observers. The main steps of the observer design and its convergence properties are illustrated through a typical problem involving an induction motor where one aims at estimating the mechanical speed, the load torque and rotor fluxes as well as the rotor inductance and resistance from the measurements of the stator currents.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.058
      Issue No: Vol. 90 (2018)
  • On the steady-state behavior of a nonlinear power system model
    • Authors: Dominic Groß; Catalin Arghir; Florian Dörfler
      Pages: 248 - 254
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Dominic Groß, Catalin Arghir, Florian Dörfler
      In this article, we consider a dynamic model of a three-phase power system including nonlinear generator dynamics, transmission line dynamics, and static nonlinear loads. We define a synchronous steady-state behavior which corresponds to the desired nominal operating point of a power system and obtain necessary and sufficient conditions on the control inputs, load model, and transmission network, under which the power system admits this steady-state behavior. We arrive at a separation between the steady-state conditions of the transmission network and generators, which allows us to recover the steady-state of the entire power system solely from a prescribed operating point of the transmission network. Moreover, we constructively obtain necessary and sufficient steady-state conditions based on network balance equations typically encountered in power flow analysis. Our analysis results in several necessary conditions that any power system control strategy needs to satisfy.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.057
      Issue No: Vol. 90 (2018)
  • Power spectrum identification for quantum linear systems
    • Authors: Matthew Levitt; Mădălin Guţă; Hendra I. Nurdin
      Pages: 255 - 262
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Matthew Levitt, Mădălin Guţă, Hendra I. Nurdin
      We investigate system identification for general quantum linear systems in the situation where the input field is prepared as stationary (squeezed) quantum noise. In this regime the output field is characterised by the power spectrum, which encodes covariance of the output state. We address which parameters can be identified from the power spectrum and how to construct a system realisation from the power spectrum. The power spectrum depends on the system parameters via the transfer function. We show that the transfer function can be uniquely recovered from the power spectrum, so that equivalent systems are related by a symplectic transformation.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.037
      Issue No: Vol. 90 (2018)
  • Cascade and locally dissipative realizations of linear quantum systems for
           pure Gaussian state covariance assignment
    • Authors: Shan Ma; Matthew J. Woolley; Ian R. Petersen; Naoki Yamamoto
      Pages: 263 - 270
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Shan Ma, Matthew J. Woolley, Ian R. Petersen, Naoki Yamamoto
      This paper presents two realizations of linear quantum systems for covariance assignment corresponding to pure Gaussian states. The first one is called a cascade realization; given any covariance matrix corresponding to a pure Gaussian state, we can construct a cascaded quantum system generating that state. The second one is called a locally dissipative realization; given a covariance matrix corresponding to a pure Gaussian state, if it satisfies certain conditions, we can construct a linear quantum system that has only local interactions with its environment and achieves the assigned covariance matrix. Both realizations are illustrated by examples from quantum optics.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.061
      Issue No: Vol. 90 (2018)
  • Image feedback based optimal control and the value of information in a
           differential game
    • Authors: Vladimir Macias; Israel Becerra; Rafael Murrieta-Cid; Hector M. Becerra; Seth Hutchinson
      Pages: 271 - 285
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Vladimir Macias, Israel Becerra, Rafael Murrieta-Cid, Hector M. Becerra, Seth Hutchinson
      In this paper, we address pursuit-evasion problems in which the pursuer is a Differential Drive Robot (DDR) that attempts to capture an omnidirectional evader. From the Nash property it follows that if the evader deviates from its maximum potential speed then the capture time shall not increase for a pursuer that does not deviate from its Nash equilibrium motion strategy. However, it is not immediately clear how the pursuer could exploit that evader’s deviation from its maximum potential speed, which might correspond to situations where the evader’s capabilities may degrade with time, for example, battery depletion in an autonomous vehicle, or fatigue in an animal evader. This can be considered as a scenario of an evader in which the set of admissible controls varies with time. In the present paper we consider such scenario. In our first result, we propose an alternative strategy for the pursuer, which, for certain scenarios, further reduces the capture time compared to the strategy based on the maximum potential evader’s speed. In our second result, we show that, under non-anticipative strategies, a pursuer strategy that uses the instantaneous evader speed alone, does not always guarantee to improve the payoff for the pursuer, nor the capture of the evader. Hence, we conclude that the evader’s location is the relevant information for the pursuer to know. Later, we present vision-based control laws that implement the optimal pursuer strategy. The optimal pursuer strategy is characterized by a partition of the reduced space (a representation of the game in the pursuer’s body-attached coordinate system) in which each region maps to an optimal pursuer action. We consider the case for which the pursuer is equipped with an omnidirectional catadioptric camera. Finally, in our third result we show that the location of the evader on the image can be directly used by the pursuer to define its motion strategy, in spite of the distortion of the state space suffered on the image. That is, the pursuer is able to apply its motion strategy using the image without explicitly reconstructing the evader’s position. This approach is computationally efficient, and robust to occlusions and noise in the image.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.045
      Issue No: Vol. 90 (2018)
  • ℋ− index for discrete-time stochastic systems with Markovian jump and
           multiplicative noise
    • Authors: Yan Li; Weihai Zhang; Xi-Kui Liu
      Pages: 286 - 293
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Yan Li, Weihai Zhang, Xi-Kui Liu
      In this paper, we discuss the ℋ − index problem for stochastic linear discrete-time systems subject to Markovian jump and multiplicative noise, for which, a necessary and sufficient condition for an ℋ − index larger than γ > 0 is given in finite time horizon. It is shown that the ℋ − index larger than a given value is equivalent to the solvability of a certain generalized difference Riccati equation (GDRE). What we have obtained generalizes the results of deterministic systems to stochastic models. Moreover, the ℋ − index problem for s q u a r e systems in infinite horizon is also studied. Finally, some examples are presented to illustrate the effectiveness of the proposed theoretical results.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.032
      Issue No: Vol. 90 (2018)
  • Sliding mode control of hybrid switched systems via an event-triggered
    • Authors: Xiaojie Su; Xinxin Liu; Peng Shi; Yong-Duan Song
      Pages: 294 - 303
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Xiaojie Su, Xinxin Liu, Peng Shi, Yong-Duan Song
      This paper is devoted to solving the problem of sliding mode control for discrete-time switched systems via an event-triggered strategy. First, a new linear switching function combined with corresponding networked sliding mode dynamics is constructed using a time-delay system design method and event-triggering scheme. Then, on the basis of the Lyapunov functional technique and the average dwell time approach, sufficient conditions for the existence of the concerned networked sliding mode control are established in terms of linear matrix inequalities. Furthermore, an event-triggered sliding mode control law is developed to drive the resultant closed-loop system trajectories into a bounded switched region and maintain them therein for subsequent periods. Finally, a verification example is given to show the effectiveness of the proposed new design techniques.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.12.033
      Issue No: Vol. 90 (2018)
  • A new integral sliding mode design method for nonlinear stochastic systems
    • Authors: Yueying Wang; Yuanqing Xia; Hongyi Li; Pingfang Zhou
      Pages: 304 - 309
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Yueying Wang, Yuanqing Xia, Hongyi Li, Pingfang Zhou
      Recently, several integral sliding mode control (ISMC) methodologies have been put forward to robust stabilization of nonlinear stochastic systems depicted by T–S fuzzy models. However, these results employ very restrictive assumptions on system matrices, which impose a great limitation to real applications. This paper aims to remove these assumptions and present a new ISMC method for fuzzy stochastic systems subjected to matched/mismatched uncertainties. To this end, a novel fuzzy integral sliding manifold function is adopted such that the matched uncertainties are completely rejected while the mismatched ones will not be enlarged during the sliding mode phase. Sufficient conditions are derived to ensure the stochastic stability of the closed-loop system under sliding motion. A fuzzy sliding mode controller is further presented to maintain the states of fuzzy stochastic system onto the predefined fuzzy manifold in the presence of uncertainties. The effectiveness and benefit of the developed new method are demonstrated by the inverted pendulum system.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.11.029
      Issue No: Vol. 90 (2018)
  • Robust stability conditions for feedback interconnections of
           distributed-parameter negative imaginary systems
    • Authors: Sei Zhen Khong; Ian R. Petersen; Anders Rantzer
      Pages: 310 - 316
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Sei Zhen Khong, Ian R. Petersen, Anders Rantzer
      Sufficient and necessary conditions for the stability of positive feedback interconnections of negative imaginary systems are derived via an integral quadratic constraint (IQC) approach. The IQC framework accommodates distributed-parameter systems with irrational transfer function representations, while generalising existing results in the literature and allowing exploitation of flexibility at zero and infinite frequencies to reduce conservatism in the analysis. The main results manifest the important property that the negative imaginariness of systems gives rise to a certain form of IQCs on positive frequencies that are bounded away from zero and infinity. Two additional sets of IQCs on the DC and instantaneous gains of the systems are shown to be sufficient and necessary for closed-loop stability along a homotopy of systems.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2017.09.010
      Issue No: Vol. 90 (2018)
  • Realization of time-delay systems
    • Authors: Arvo Kaldmäe; Ülle Kotta
      Pages: 317 - 320
      Abstract: Publication date: April 2018
      Source:Automatica, Volume 90
      Author(s): Arvo Kaldmäe, Ülle Kotta
      The paper addresses the problem of transforming a single-input single-output nonlinear retarded time-delay system, described by an input–output equation, in the traditional observable state space form. The solution is generalized from the delay-free case and depends on integrability of certain submodule of differential 1-forms. The integrability conditions are improved to make them constructive. Finally, it is explained why one may obtain two realizations, which are not connected by bi-causal change of state coordinates.

      PubDate: 2018-02-26T11:42:52Z
      DOI: 10.1016/j.automatica.2018.01.001
      Issue No: Vol. 90 (2018)
  • Co-design of linear systems using Generalized Benders Decomposition
    • Authors: Prasad Vilas Chanekar; Nikhil Chopra; Shapour Azarm
      Pages: 180 - 193
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Prasad Vilas Chanekar, Nikhil Chopra, Shapour Azarm
      Design of a physical system and its controller has significant ramifications on the overall system performance. The traditional approach of first optimizing the physical design and then the controller may lead to sub-optimal solutions. This is due to the interdependence between the physical design and control parameters through the dynamic equations. Recognition of this fact paved the way for investigation into the “Co-Design” research theme wherein the overall system’s physical design and control are simultaneously optimized. In this paper, a novel approach to address the co-design problem for a class of Linear Time Invariant (LTI) dynamic systems controlled by a Linear Quadratic Regulator (LQR) feedback is presented. The considered co-design problem is formulated as a non-convex optimization problem with Algebraic Riccati Equation (ARE) constraint and convex design objective function. Using Semi-Definite Programming (SDP) duality, the ARE constraint is reduced into equivalent Bilinear Matrix Inequality (BMI) constraints. This reformulated co-design problem is solved using an iterative algorithm based on the Generalized Benders Decomposition (GBD) and Gradient Projection Method. The proposed algorithm converges to a solution which is within a specified tolerance from the nearest local minimum (in special cases global minimum) in a finite number of iterations. Necessary and sufficient conditions are developed to test minimality. Three examples are presented to show efficacy of the proposed algorithm.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.009
      Issue No: Vol. 89 (2018)
  • Chattering in the Reach Control Problem
    • Authors: Melkior Ornik; Mireille E. Broucke
      Pages: 201 - 211
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Melkior Ornik, Mireille E. Broucke
      The Reach Control Problem (RCP) is a fundamental problem in hybrid control theory. The goal of the RCP is to find a feedback control that drives the state trajectories of an affine system to leave a polytope through a predetermined exit facet. In the current literature, the notion of leaving a polytope through a facet has an ambiguous definition. There are two different notions. In one, at the last time instance when the trajectory is inside the polytope, it must also be inside the exit facet. In the other, the trajectory is required to cross from the polytope into the outer open half-space bounded by the exit facet. In this paper, we provide a counterexample showing that these definitions are not equivalent for general continuous or smooth state feedback. On the other hand, we prove that analyticity of the feedback control is a sufficient condition for equivalence of these definitions. We generalize this result to several other classes of feedback control previously investigated in the RCP literature, most notably piecewise affine feedback. Additionally, we clarify or complete a number of previous results on the exit behaviour of trajectories in the RCP.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.11.008
      Issue No: Vol. 89 (2018)
  • Open-loop asymptotically efficient model reduction with the
           Steiglitz–McBride method
    • Authors: Niklas Everitt; Miguel Galrinho; Håkan Hjalmarsson
      Pages: 221 - 234
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Niklas Everitt, Miguel Galrinho, Håkan Hjalmarsson
      In system identification, it is often difficult to use a physical intuition when choosing a noise model structure. The importance of this choice is that, for the prediction error method (PEM) to provide asymptotically efficient estimates, the model orders must be chosen according to the true system. However, if only the plant estimates are of interest and the experiment is performed in open loop, the noise model can be over-parameterized without affecting the asymptotic properties of the plant. The limitation is that, as PEM suffers in general from non-convexity, estimating an unnecessarily large number of parameters will increase the risk of getting trapped in local minima. Here, we consider the following alternative approach. First, estimate a high-order ARX model with least squares, providing non-parametric estimates of the plant and noise model. Second, reduce the high-order model to obtain a parametric model of the plant only. We review existing methods to do this, pointing out limitations and connections between them. Then, we propose a method that connects favorable properties from the previously reviewed approaches. We show that the proposed method provides asymptotically efficient estimates of the plant with open-loop data. Finally, we perform a simulation study suggesting that the proposed method is competitive with state-of-the-art methods.

      PubDate: 2018-02-05T13:39:39Z
      DOI: 10.1016/j.automatica.2017.12.016
      Issue No: Vol. 89 (2018)
  • Stability structures of conjunctive Boolean networks
    • Authors: Zuguang Gao; Xudong Chen; Tamer Başar
      Pages: 8 - 20
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Zuguang Gao, Xudong Chen, Tamer Başar
      A Boolean network is a finite dynamical system, whose variables take values from a binary set. The value update rule for each variable is a Boolean function, depending on a selected subset of variables. Boolean networks have been widely used in modeling gene regulatory networks. We focus in this paper on a special class of Boolean networks, termed as conjunctive Boolean networks. A Boolean network is conjunctive if the associated value update rule is comprised of only AND operations. It is known that any trajectory of a finite dynamical system will enter a periodic orbit. We characterize in this paper all periodic orbits of a conjunctive Boolean network whose underlying graph is strongly connected. In particular, we establish a bijection between the set of periodic orbits and the set of binary necklaces of a certain length. We further investigate the stability of a periodic orbit. Specifically, we perturb a state in the periodic orbit by changing the value of a single entry of the state. The trajectory, with the perturbed state being the initial condition, will enter another (possibly the same) periodic orbit in finite time steps. We then provide a complete characterization of all such transitions from one periodic orbit to another. In particular, we construct a digraph, with the vertices being the periodic orbits, and the (directed) edges representing the transitions among the orbits. We call such a digraph the stability structure of the conjunctive Boolean network.

      PubDate: 2017-12-27T01:39:22Z
      DOI: 10.1016/j.automatica.2017.11.017
      Issue No: Vol. 89 (2017)
  • Stochastic control for optical manipulation of multiple microscopic
    • Authors: Quang Minh Ta; Chien Chern Cheah
      Pages: 52 - 64
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Quang Minh Ta, Chien Chern Cheah
      While various control techniques have been developed for optical manipulation, the Brownian movement of microscopic objects in the medium is usually ignored for simplicity of analyzing the control systems. Nevertheless, due to the universality of the Brownian movement and its effect on optical manipulation of cells or micro-objects, it is required for the Brownian effect to be properly taken into consideration so as to ensure the stability and performance of the control systems. In this paper, we derive a stochastic control technique to achieve a theoretical framework for optical manipulation of multiple microscopic objects in the presence of the Brownian perturbations. In the proposed control methodology, a region control technique and a dynamic interaction approach are developed for collision-free manipulation of the target micro-objects with random perturbations. All the target micro-objects are trapped and manipulated simultaneously while being kept inside the desired dynamic region, and at the same time, preserving a minimum distance with each other to avoid collisions. While a bounded tracking or region error exists in current control techniques for optical manipulation due to the effect of the Brownian perturbations, this paper provides a new approach which guarantees that all the target micro-objects are kept inside the desired region during the course of manipulation. Rigorous mathematical formulation has been developed for automated manipulation of multiple microscopic objects in the presence of the Brownian perturbations, and experimental results are presented to demonstrate the feasibility and effectiveness of the proposed control technique.

      PubDate: 2017-12-27T01:39:22Z
      DOI: 10.1016/j.automatica.2017.11.031
      Issue No: Vol. 89 (2017)
  • Global optimization for low-dimensional switching linear regression and
           bounded-error estimation
    • Authors: Fabien Lauer
      Pages: 73 - 82
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Fabien Lauer
      The paper provides global optimization algorithms for two particularly difficult nonconvex problems raised by hybrid system identification: switching linear regression and bounded-error estimation. While most works focus on local optimization heuristics without global optimality guarantees or with guarantees valid only under restrictive conditions, the proposed approach always yields a solution with a certificate of global optimality. This approach relies on a branch-and-bound strategy for which we devise lower bounds that can be efficiently computed. In order to obtain scalable algorithms with respect to the number of data, we directly optimize the model parameters in a continuous optimization setting without involving integer variables. Numerical experiments show that the proposed algorithms offer a higher accuracy than convex relaxations with a reasonable computational burden for hybrid system identification. In addition, we discuss how bounded-error estimation is related to robust estimation in the presence of outliers and exact recovery under sparse noise, for which we also obtain promising numerical results.

      PubDate: 2017-12-27T01:39:22Z
      DOI: 10.1016/j.automatica.2017.11.026
      Issue No: Vol. 89 (2017)
  • A peak-over-threshold search method for global optimization
    • Authors: Siyang Gao; Leyuan Shi; Zhengjun Zhang
      Pages: 83 - 91
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Siyang Gao, Leyuan Shi, Zhengjun Zhang
      In this paper, we propose a random search method, called peak-over-threshold search (POTS), for solving global optimization problems. An important feature of POTS is that it combines the existing partition-based random search framework (e.g., Shi and Ólafsson 2000a; Chen et al. 2011) with the peak-over-threshold statistical reference (Coles, 2001) in order to achieve high search efficiency. In each iteration, POTS partitions the solution space into several subregions, evaluates the quality of each subregion and moves to promising subregions for more partitioning and sampling. To effectively assess the quality of a subregion, an extreme value type of inference in statistics is used to develop a new promising index which reflects the optimal objective value of a subregion and biases the search to regions that are likely to contain the optimal or near-optimal solutions. Under assumptions on the depth of partitioning and the probability of correct movement, POTS is shown to converge with probability one to the optimal region. The higher efficiency of the proposed method is illustrated by numerical examples. The application of POTS to beam angle selection, an important optimization problem in radiation treatment, is also presented in this paper.

      PubDate: 2017-12-27T01:39:22Z
      DOI: 10.1016/j.automatica.2017.12.002
      Issue No: Vol. 89 (2017)
  • Practical closed-loop dynamic pricing in smart grid for supply and demand
    • Authors: Jianping He; Chengcheng Zhao; Lin Cai; Peng Cheng; Ling Shi
      Pages: 92 - 102
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Jianping He, Chengcheng Zhao, Lin Cai, Peng Cheng, Ling Shi
      Pricing strategy for power systems is an important and challenging problem, due to the difficulties in predicting the demand and the reactions of customers to the price accurately. Any prediction errors may result in higher costs to the supplier. To address this issue, in this paper, we propose a novel, practical closed-loop pricing algorithm (PCPA). Using the closed-loop control to well coordinate the customers and the supplier, the power system can run more efficiently, resulting in both cost saving for customers and higher profit for the supplier. We prove the convergence of PCPA, i.e., a stable price can be achieved. We provide sufficient conditions to guarantee the win-win solution for both the customers and the supplier, and an upper bound of the gain. We also provide a necessary and sufficient condition of that the highest win for both the customers and the supplier can be achieved. Extensive simulations have shown that PCPA can outperform the existing prediction-based pricing algorithms. It shows that the profit gain of the proposed algorithm can up to 100% when the total demand can be fixed to the optimal demand.

      PubDate: 2017-12-27T01:39:22Z
      DOI: 10.1016/j.automatica.2017.11.011
      Issue No: Vol. 89 (2017)
  • Point-to-point iterative learning model predictive control
    • Authors: Se-Kyu Oh; Byung Jun Park; Jong Min Lee
      Pages: 135 - 143
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Se-Kyu Oh, Byung Jun Park, Jong Min Lee
      Iterative learning model predictive control (ILMPC) is a technique that combines iterative learning control (ILC) and model predictive control (MPC). The objective is to track a reference trajectory of repetitive processes on a finite time interval while rejecting real-time disturbances. In many repetitive processes, the output is not required to track all the points of a reference trajectory. In this study, we propose a point-to-point ILMPC (PTP ILMPC) technique considering only the desired reference points, and not an entire reference trajectory. In this method, an arbitrary reference trajectory passing through the desired reference values need not be generated. Numerical examples are provided to demonstrate the performances of the suggested approach in terms of PTP tracking, iterative learning, constraint handling, and real-time disturbance rejection.

      PubDate: 2017-12-27T01:39:22Z
      DOI: 10.1016/j.automatica.2017.11.010
      Issue No: Vol. 89 (2017)
  • Dominant eigenvalue minimization with trace preserving diagonal
           perturbation: Subset design problem
    • Authors: Jackeline Abad Torres; Sandip Roy
      Pages: 160 - 168
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Jackeline Abad Torres, Sandip Roy
      Motivated by network resource allocation needs, we study the problem of minimizing the dominant eigenvalue of an essentially-nonnegative matrix with respect to a trace-preserving or fixed-trace diagonal perturbation, in the case where only a subset of the diagonal entries can be perturbed. Graph-theoretic characterizations of the optimal subset design are obtained: in particular, the design is connected to the structure of a reduced effective graph defined from the essentially-nonnegative matrix. Also, the change in the optimum is studied when additional diagonal entries are constrained to be undesignable, from both an algebraic and graph-theoretic perspective. These results are developed in part using properties of the Perron complement of nonnegative matrices, and the concept of line-sum symmetry. Some results apply to general essentially-nonnegative matrices, while others are specialized for sub-classes (e.g., diagonally-symmetrizable, or having a single node cut).

      PubDate: 2017-12-27T01:39:22Z
      DOI: 10.1016/j.automatica.2017.12.007
      Issue No: Vol. 89 (2017)
  • Optimal identification experiment design for the interconnection of
           locally controlled systems
    • Authors: Xavier Bombois; Anton Korniienko; Håkan Hjalmarsson; Gérard Scorletti
      Pages: 169 - 179
      Abstract: Publication date: March 2018
      Source:Automatica, Volume 89
      Author(s): Xavier Bombois, Anton Korniienko, Håkan Hjalmarsson, Gérard Scorletti
      This paper considers the identification of the modules of a network of locally controlled systems (multi-agent systems). Its main contribution is to determine the least perturbing identification experiment that will nevertheless lead to sufficiently accurate models of each module for the global performance of the network to be improved by a redesign of the decentralized controllers. Another contribution is to determine the experimental conditions under which sufficiently informative data (i.e. data leading to a consistent estimate) can be collected for the identification of any module in such a network.

      PubDate: 2017-12-27T01:39:22Z
      DOI: 10.1016/j.automatica.2017.12.014
      Issue No: Vol. 89 (2017)
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