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  Subjects -> COMPUTER SCIENCE (Total: 2122 journals)
    - ANIMATION AND SIMULATION (31 journals)
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COMPUTER SCIENCE (1231 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 24)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 31)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 17)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 9)
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: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 16)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 7)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 6)
ACM Transactions on Economics and Computation     Hybrid Journal   (Followers: 2)
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 20)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 5)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 35)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 10)
Advanced Engineering Materials     Hybrid Journal   (Followers: 29)
Advanced Science Letters     Full-text available via subscription   (Followers: 11)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 6)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 19)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Computer Science : an International Journal     Open Access   (Followers: 14)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 59)
Advances in Engineering Software     Hybrid Journal   (Followers: 28)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 14)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Human-Computer Interaction     Open Access   (Followers: 21)
Advances in Materials Science     Open Access   (Followers: 15)
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: 51)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 6)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 9)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal   (Followers: 1)
Air, Soil & Water Research     Open Access   (Followers: 14)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 7)
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: 6)
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: 4)
Annals of Data Science     Hybrid Journal   (Followers: 12)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 3)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annals of West University of Timisoara - Mathematics and Computer Science     Open Access  
Annual Reviews in Control     Hybrid Journal   (Followers: 8)
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: 12)
Applied Categorical Structures     Hybrid Journal   (Followers: 5)
Applied Clinical Informatics     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 14)
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: 11)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 17)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 7)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 6)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 153)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 6)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 8)
Artifact     Open Access   (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 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: 6)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 12)
Automation in Construction     Hybrid Journal   (Followers: 7)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Balkan Journal of Electrical and Computer Engineering     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 51)
Big Data and Cognitive Computing     Open Access   (Followers: 3)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 327)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
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: 51)
British Journal of Educational Technology     Hybrid Journal   (Followers: 160)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 12)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal   (Followers: 2)
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 15)
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: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 15)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 8)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Hybrid Journal   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Clinical eHealth     Open Access  
Cluster Computing     Hybrid Journal   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 3)
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: 13)
Communication Theory     Hybrid Journal   (Followers: 24)
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 Information Science and Management Engineering     Open Access   (Followers: 4)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 4)
Communications of the ACM     Full-text available via subscription   (Followers: 51)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
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: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 3)
Computational and Mathematical Biophysics     Open Access   (Followers: 1)
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: 1)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access   (Followers: 1)
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 17)
Computational Linguistics     Open Access   (Followers: 24)
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: 8)
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: 35)
Computer     Full-text available via subscription   (Followers: 105)
Computer Aided Surgery     Open Access   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 16)

        1 2 3 4 5 6 7 | Last

Journal Cover
Annual Reviews in Control
Journal Prestige (SJR): 0.824
Citation Impact (citeScore): 3
Number of Followers: 8  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1367-5788
Published by Elsevier Homepage  [3161 journals]
  • Challenges for the cyber-physical manufacturing enterprises of the future
    • Abstract: Publication date: Available online 19 February 2019Source: Annual Reviews in ControlAuthor(s): Hervé Panetto, Benoit Iung, Dmitry Ivanov, Georg Weichhart, Xiaofan Wang This paper summarizes a vision of the challenges facing the so-called “Industry of the Future” as studied by the research community of the IFAC Coordinating Committee 5 on Manufacturing and Logistics Systems, which includes four Technical Committees (TC). Each TC brings its own vision and puts forward trends and issues important and relevant for future research. The analysis is performed on the enterprise-level topics with an interface too other relevant systems (e.g., supply chains). The vision developed might lead to the identification of new scientific control directions such as Industry 4.0 technology-enabled new production strategies that require highly customised supply network control, the creation of resilient enterprise to cope with risks, developments in management decision-support systems for the design, and scheduling and control of resilient and digital manufacturing networks, and collaborative control. Cobots, augmented reality and adaptable workstations are a few examples of how production and logistic systems are changing supporting the operator 4.0. Sustainable manufacturing techniques, such closed-loop supply chains, is another trend in this area. Due to increasing number of elements and systems, complex and heterogeneous enterprise systems need to be considered (e.g., for decision-making). These systems are heterogeneous and build by different stakeholders. To make use of these, an environment is needed that allows the integration of the systems forming a System-of-Systems (SoS). The changing environment requires models which adapt over time. Some of the adaptation is due to learning, other mechanisms include self-organisation by intelligent agents. In general, models and systems need to be modular and support modification and (self-)adaptation. An infrastructure is needed that supports loose coupling and evolving systems of systems. The vision of the overall contribution from the research community in manufacturing and logistics systems, over the next few years is to bring together researchers and practitioners presenting and discussing topics in modern manufacturing modelling, management and control in the emerging field of Industry 4.0-based resilient and innovative production SoS and supply networks.
  • Ubiquitous knowledge empowers the Smart Factory: The impacts of a
           Service-oriented Digital Twin on enterprises' performance
    • Abstract: Publication date: Available online 10 February 2019Source: Annual Reviews in ControlAuthor(s): Francesco Longo, Letizia Nicoletti, Antonio Padovano While the Industry 4.0 is idolizing the potential of an artificial intelligence embedded into ``things", it is neglecting the role of the human component, which is still indispensable in different manufacturing activities, such as a machine setup or maintenance operations. The present research study first proposes an Industrial Internet pyramid as emergent human-centric manufacturing paradigm within Industry 4.0 in which central is the role of a Ubiquitous Knowledge about the manufacturing system intuitively accessed and used by the manufacturing employees. Second, the prototype of a Service-oriented Digital Twin, which leverage on a flexible ontology-oriented knowledge structure and on augmented reality combined to a vocal interaction system for an intuitive knowledge retrieval and fruition, has been designed and developed to deliver this manufacturing knowledge. Two test-beds, complimentary for the problems in practice (the former on the maintenance-production interface in a large enterprise, the latter majorly focused in production and setups in a small and medium enterprise), show the significant benefits in terms of time, costs and process quality, thus validating the approach proposed. This research shows that a human-centric and knowledge-driven approach can drive the performance of Industry 4.0 initiatives and lead a Smart Factory towards its full potential.
  • Fundamentals of smart manufacturing: A multi-thread perspective
    • Abstract: Publication date: Available online 8 February 2019Source: Annual Reviews in ControlAuthor(s): Andrew Kusiak The paper outlines key characteristics of smart manufacturing, data-driven, networked, connected, resource sharing, resilient, and sustainable. Manufacturing resiliency and sustainability have received limited attention in the literature and they are the focus of this paper. Both are related and offer challenges that may become differentiators of smart manufacturing. Resiliency provides businesses with defenses against natural and human caused adversities. The list of attributes provided in the paper is intended for comprehensive assessment of manufacturing resiliency. Solutions are needed to make businesses more resilient and sustainable. Research on business models equating sustainability with an industrial activity is suggested. A scheme for labeling environmental friendliness of materials makes as a token contribution to sustainability.
  • Near-optimal control of nonlinear dynamical systems: A brief survey
    • Abstract: Publication date: Available online 6 February 2019Source: Annual Reviews in ControlAuthor(s): Yinyan Zhang, Shuai Li, Liefa Liao For nonlinear dynamical systems, an optimal control problem generally requires solving a partial differential equation called the Hamilton–Jacobi–Bellman equation, the analytical solution of which generally cannot be obtained. However, the demand for optimal control keeps increasing, with the goal to save energy, reduce transient time, minimize error accumulation, etc. Consequently, methods were reported to approximately solve the problem leading to the so-called near-optimal control, although their technical details differ. This research direction has experienced great progress in recent years but a timely review of it is still missing. This paper serves as a brief survey for existing methods in this research direction.
  • A comprehensive survey on control strategies of distributed generation
           power systems under normal and abnormal conditions
    • Abstract: Publication date: Available online 19 December 2018Source: Annual Reviews in ControlAuthor(s): Mehmet Emin Meral, Doğan Çelík High energy demand, low cost requirements and higher reliability requirements increase the importance of distributed generation power systems (DGPSs). The large capacity DGPSs requires high performance control algorithms and synchronization techniques based positive-negative sequence (PNS) extractors to fulfil system reliability and power quality requirements under not only during normal operating conditions, but also under unbalanced grid conditions. The power quality problems caused by voltage unbalances, voltage sag/swell, voltage fluctuations, phase faults and harmonic distortions have critical influences on control of power converter devices interfaced DGPSs. In literature studies, novel control strategies with phase locked loops (PLLs) techniques based PNS extractors are used to overcome these problems. In this paper, a comprehensive review on various advanced control strategies and PNS extractors for interlinking three phase inverter in the DGPSs are comprehensively investigated and discussed under normal and abnormal conditions. Several PNS extractors have been overviewed to produce the sequences components required for reference current generation (RCG). The theoretical assessment of the RCG based flexible control strategies and overcurrent limitation control are also comprehensively analysed, surveyed and compared in detail to deal with power quality problems. Comparative analyses for PNS extractors, voltage/current regulation controllers and RCG based control strategies have been detailed presented and analysed. The presented detailed overview can be useful to researchers studying impact of normal and abnormal conditions on various control strategies with or without any using PLLs based PNS extractors for three-phase inverters interfaced DGPSs.
  • Conic optimization for control, energy systems, and machine learning:
           Applications and algorithms
    • Abstract: Publication date: Available online 5 December 2018Source: Annual Reviews in ControlAuthor(s): Richard Y. Zhang, Cédric Josz, Somayeh Sojoudi Optimization is at the core of control theory and appears in several areas of this field, such as optimal control, distributed control, system identification, robust control, state estimation, model predictive control and dynamic programming. The recent advances in various topics of modern optimization have also been revamping the area of machine learning. Motivated by the crucial role of optimization theory in the design, analysis, control and operation of real-world systems, this tutorial paper offers a detailed overview of some major advances in this area, namely conic optimization and its emerging applications. First, we discuss the importance of conic optimization in different areas. Then, we explain seminal results on the design of hierarchies of convex relaxations for a wide range of nonconvex problems. Finally, we study different numerical algorithms for large-scale conic optimization problems.
  • Automated learning with a probabilistic programming language: Birch
    • Abstract: Publication date: Available online 16 November 2018Source: Annual Reviews in ControlAuthor(s): Lawrence M. Murray, Thomas B. Schön This work offers a broad perspective on probabilistic modeling and inference in light of recent advances in probabilistic programming, in which models are formally expressed in Turing-complete programming languages. We consider a typical workflow and how probabilistic programming languages can help to automate this workflow, especially in the matching of models with inference methods. We focus on two properties of a model that are critical in this matching: its structure—the conditional dependencies between random variables—and its form—the precise mathematical definition of those dependencies. While the structure and form of a probabilistic model are often fixed a priori, it is a curiosity of probabilistic programming that they need not be, and may instead vary according to random choices made during program execution. We introduce a formal description of models expressed as programs, and discuss some of the ways in which probabilistic programming languages can reveal the structure and form of these, in order to tailor inference methods. We demonstrate the ideas with a new probabilistic programming language called Birch, with a multiple object tracking example.
  • An approach to support Industry 4.0 adoption in SMEs using a
    • Abstract: Publication date: Available online 12 November 2018Source: Annual Reviews in ControlAuthor(s): Michele Dassisti, Antonio Giovannini, Pasquale Merla, Michela Chimienti, Hervé Panetto Despite the recent growing interest in the “factory smartness”, still there are only few small and medium enterprises (SMEs) that adopt effective Industry 4.0 (I4.0) solutions. The main reasons can be related to the lack of formalized processes, lack of ICT knowledgeas well as low-cost commercial systems.To cope with these issues, this work focuses on the development and the application of an approach to provide SMEs with a multi-purpose, modular, knowledge-based system: the main aim is to provide a modular and extensible system that can be incrementally implemented without requiring huge initial investments.This system is based on a core design-knowledge meta-model. From this core meta-model, multi-purposes modules can be built: in this paper, we present modules for the traceability support, the AR-powered assembly support, the machine-to-machine control and the data analysis support.
  • Microgrid modelling: A comprehensive survey
    • Abstract: Publication date: Available online 26 October 2018Source: Annual Reviews in ControlAuthor(s): Sachidananda Sen, Vishal Kumar With the advent of visions on smart grid (SG) technology, the researches in this field are growing at a steady pace. Small, controlled, and clustered units in the distribution network called “Microgrids” (MGs) are regarded as the best possible way to achieve SG features. Modelling, control, stability study, monitoring and protection are the main areas undergoing research in MGs. As several components are integrated together to form a MG viz. microsources (MSs), loads, storage units, power electronics (PE) converters, etc., its modelling leads to a higher order system also known as the “Large-scale system”. Hence, to decrease the handling burden, several modelling schemes are involved to get the reduced order models (ROMs) of MGs. This paper provides a comprehensive survey of existing MG models as well as discusses the principles behind, and their applicability. The process of stochastic and predictive modelling along with a method for classification of various modelling techniques under four categories viz. component-wise, single entity or lumped, stochastic modelling and dynamic equivalence are also presented. Further, several research challenges are suggested, where the findings on lower order reduced models obtained by the application of model order reduction (MOR) techniques and dynamic equivalence principles are also reported.
  • Data-driven control in marine systems
    • Abstract: Publication date: Available online 22 October 2018Source: Annual Reviews in ControlAuthor(s): Vahid Hassani, António M. Pascoal, Tord F. Onstein With the advent of cheap smart sensors installed on board marine vehicles and the increasing computational power of small embedded processors there is tremendous potential for the implementation of new strategies to control marine systems on the basis of input-output plant data. The emerging field of smart sensors affords a unique opportunity to have access to on-line measurement of dynamical systems’ variables seamlessly, at a low price. By applying a data-driven control algorithm to a marine vehicle, the paper introduces a new perspective on how data can be used in the control loop in marine systems. Classical control methodologies start by developing a model of the plant to be controlled, after which a number of control design techniques can be used. Recent advances in so-called model-free data-driven control methodologies, in particular unfalsified control, hold promise to merge the identification and control phases. Unfalsified control techniques build on the construction of a bank of controllers for a given plant, in which there exists at least one controller that meets the desired performance specification and a falsification unit. The latter is implemented using a cost function that directly evaluates the performance of the controllers (in and out of the feedback loop) using measured input and output data. At each sampling time, the performance of the controllers is assessed and the controllers that do not meet the pre-defined performance specification criteria will be falsified and removed from the bank of the controllers, after which an active controller will be selected among the unfalsified ones. In this paper, by presenting the results of the application of unfalsified control to the problem of Dynamic Positioning (DP) of marine vessels subjected to environmental forces, we aim to attract the attention of researchers in the field of marine control to the new perspective of using data to directly control marine system.
  • Reinforcement learning for control: Performance, stability, and deep
    • Abstract: Publication date: Available online 19 October 2018Source: Annual Reviews in ControlAuthor(s): Lucian Buşoniu, Tim de Bruin, Domagoj Tolić, Jens Kober, Ivana Palunko Reinforcement learning (RL) offers powerful algorithms to search for optimal controllers of systems with nonlinear, possibly stochastic dynamics that are unknown or highly uncertain. This review mainly covers artificial-intelligence approaches to RL, from the viewpoint of the control engineer. We explain how approximate representations of the solution make RL feasible for problems with continuous states and control actions. Stability is a central concern in control, and we argue that while the control-theoretic RL subfield called adaptive dynamic programming is dedicated to it, stability of RL largely remains an open question. We also cover in detail the case where deep neural networks are used for approximation, leading to the field of deep RL, which has shown great success in recent years. With the control practitioner in mind, we outline opportunities and pitfalls of deep RL; and we close the survey with an outlook that – among other things – points out some avenues for bridging the gap between control and artificial-intelligence RL techniques.
  • An autonomous underwater vehicle and SUNSET to bridge underwater networks
           composed of multi-vendor modems
    • Abstract: Publication date: Available online 19 October 2018Source: Annual Reviews in ControlAuthor(s): Alessandro Ridolfi, Daniele Spaccini, Francesco Fanelli, Matteo Franchi, Niccolò Monni, Luigi Picari, Chiara Petrioli, Benedetto Allotta Nowadays, underwater acoustic communication is an interesting topic of research. This is especially true in the case of Autonomous Underwater Vehicles (AUVs): due to the limitations of the underwater environment, where WiFi and radio communications are limited, it is very important to rely on efficient and reliable tools for acoustic data exchange. Indeed, an underwater network of acoustic nodes can enhance the navigation and localization capabilities of one or more vehicles. However, cooperation and networking is not feasible in underwater networks composed of vehicles with different software architecture and multi-vendor modems due to the lack of communication standards. In this paper, the authors investigate the use of an AUV as a mobile bridging node within a network of fixed heterogeneous acoustic modems. In particular, MARTA AUV, developed and built by the Department of Industrial Engineering of the University of Florence, is employed to enable data transmission between modems of different manufacturers. The networking and the handling of multiple and multi-vendor modems are instead performed through the SUNSET Software Defined Communication Stack (SDCS) framework, developed by University of Rome La Sapienza jointly with WSENSE Srl. Different bridging tests have been performed in field to evaluate the feasibility of such approach, showing that AUVs can efficiently accomplish the role of gateway between the nodes of the network communicating through the SUNSET SDCS framework.
  • A review of quadrotor: An underactuated mechanical system
    • Abstract: Publication date: Available online 19 October 2018Source: Annual Reviews in ControlAuthor(s): Bara J. Emran, Homayoun Najjaran This review concentrates on three main challenges of controlling a quadrotor unmanned aerial vehicle (UAV) as an underactuated mechanical system (UMS). The challenges include underactuation, model uncertainty, and actuator failure. The review also illustrates the state of the quadrotor control research in an attempt to find practical solutions for those challenges. By definition, a UMS has less number of control actions than the number of degrees of freedom to be controlled. Hence, traditional control strategies developed for fully actuated systems are not directly applicable to UMS. Research on UMS is one of the most interesting topics in the robotics and control community because of its relevance to a variety of applications. Examples include humanoid robots and most aerial and underwater vehicles. However similar to any other nonlinear systems, the stability and control of quadrotors suffer from intrinsic complexities exasperated by underactuation, model uncertainties and actuator failure. In this review article, we are going to address these problems and discuss the solutions mostly concerning the application of different control strategies presented in recent literature. We also present the frontiers and research directions towards improving performance of quadrotors for emerging and complex applications.
  • Introduction to the special section on marine and maritime robotics:
           innovation and challenges
    • Abstract: Publication date: Available online 19 October 2018Source: Annual Reviews in ControlAuthor(s): Marco Bibuli, Enrica Zereik
  • Challenges and future trends in marine robotics
    • Abstract: Publication date: Available online 12 October 2018Source: Annual Reviews in ControlAuthor(s): Enrica Zereik, Marco Bibuli, Nikola Mišković, Pere Ridao, António Pascoal Spawned by fast paced progress in marine science and technology, the past two decades have witnessed growing interest in ocean exploration and exploitation for scientific and commercial purposes, the development of technological products for the maritime and offshore industries, and a host of other activities in which the marine environment takes center stage. In this context, marine robotics has steadily emerged as a key enabling technology for the execution of increasingly complex and challenging missions at sea. Intensive research and development in this field have led to major advances and shown unequivocally the effectiveness and reliability of marine robotics solutions in several domains. This progress goes hand in hand with the availability of increasingly sophisticated acoustic networks for multiple, cooperative missions involving surface and underwater robots. At the root of this trend is the fruitful dialogue between robotic systems developers and end-users with the capacity to convert general mission objectives into functional and technical specifications that serve as application-driven requirements for engineering development. The result is the tremendous progress observed in the consolidated methodologies and procedures adopted and the consequent impact on science, industry, and the society at large. In spite of the progress in the area, however many challenges must still be faced and novel applications will continue to set further requirements for future generations of marine robots and their enabling systems. The time is therefore appropriate to overview recent trends in the field of marine robotics and assess their impact on several important application domains. With these objectives in mind, in the present paper we highlight key technological achievements in the field, analyze some of the shortcomings encountered, and indicate specific issues that warrant further research and development effort. To this end, we review a number of highly representative projects in the field, with due account for the theoretical frameworks upon which technological developments build upon. Finally, the paper concludes with an outlook on the future of marine robotics, both from a theoretical and practical standpoint, and describes recently initiated projects that hold promise for the development of advanced tools and systems for ocean exploration and exploitation.
  • Experimental investigation of locomotion efficiency and path-following for
           underwater snake robots with and without a caudal fin
    • Abstract: Publication date: Available online 11 October 2018Source: Annual Reviews in ControlAuthor(s): E. Kelasidi, A.M. Kohl, K.Y. Pettersen, B.H. Hoffmann, J.T. Gravdahl Over the last few decades, the robotics community has shown increasing interest in developing bioinspired swimming robots, driven by the need for more economical, more efficient, autonomous, highly flexible and maneuverable robotic systems for underwater operations. In this paper, we present a bioinspired underwater snake robot (USR) equipped with a passive caudal (tail) fin. In particular, a highly flexible USR configuration is presented that is capable of locomotion both on the ground and underwater due to its robust mechanical and modular design, which allows additional effectors to be attached to different modules of the robot depending on the requirements of the application. This provides flexibility to the operator, who can thus choose the proper configuration depending on the task to be performed in various uncertain environments on the ground and underwater. Experimental results on locomotion efficiency and path-following control are obtained for a physical USR to enable a comparison of the USR motion with and without the passive caudal fin, for both lateral undulation and eel-like motion patterns. Results comparing the locomotion efficiency in both simulations and experiments are presented in order to validate the proposed models for USRs. By means of fluid parameter identification, both a qualitative and a quantitative comparison between the simulated and experimental results are performed regarding the achieved forward velocity. Furthermore, the experimental results show that a path-following control approach that has previously been proposed for USRs without a caudal fin can be directly applied to solve the path-following control problem for this bioinspired USR with a passive caudal fin. In particular, it is shown that this path-following control approach successfully steers the robot toward and along the desired path, and furthermore, the results show that it is possible to almost double the forward velocity of the robot by using a passive caudal fin.
  • Multiple autonomous surface vehicle motion planning for cooperative
           range-based underwater target localization
    • Abstract: Publication date: Available online 11 October 2018Source: Annual Reviews in ControlAuthor(s): N. Crasta, D. Moreno-Salinas, A.M. Pascoal, J. Aranda Range-based target localization is an important class of problems that arise in an increasing number of scientific and commercial missions at sea. Underwater target localization refers to the task of estimating the positions of fixed or moving underwater targets by using range measurements between the targets and one or more autonomous surface vehicles (ASVs), called trackers, undergoing trajectories that are known in real time. In this context, the trackers must execute sufficiently exciting maneuvers so as to maximize the range-based information available for multiple target localization. In this paper, adopting an estimation theoretical setting, we first propose a general methodology for tracker motion planning that results from maximizing the determinant of an appropriately defined Fisher information matrix (FIM) subject to inter-vehicle collision avoidance and vehicle maneuvering constraints. Then, for the single-target single-tracker problem (which is the dual problem of the classical single-beacon navigation problem), we provide a family of analytical solutions for the optimal tracker trajectories and complement the results with a practical experiment using a tracker when the target undergoes trajectories that are straight lines, pieces of arcs, or a combination thereof. In the methodology adopted for system implementation the tracker runs three key algorithms simultaneously, over a sliding time window: (i) tracker motion planning, (ii) tracker motion control, and (iii) target motion estimation based on range data acquired on-line.In order to simplify the types of trajectories that the tracker must undergo in the single target localization problem, we extend the above set-up to the case where the tracker works in cooperation with another vehicle, called companion, that can also measure ranges to the target and share this info with the tracker. The latter may have access to the position of the companion or, in some cases, only to the range between the two vehicles. We consider three different operating scenarios where the motion of the tracker is chosen so as to increase the accuracy with which the position of the target can be estimated. The scenarios reflect the situations where the motion of the companion vehicle satisfies one of three conditions: (i) the motion is not defined a priori and can also be optimized, (ii) the motion is fixed a priori and is known to the tracker (scenario in which the tracker benefits from the extra information acquired by the companion vehicle, which tracks a desired trajectory in the context of a separate, independent mission), and (iii) the motion is not known a priori and must be learned in the course of the mission. Simulation results illustrate the methodology adopted for cooperative target localization.
  • Towards an autonomous underwater vehicles test range: At-sea
           experimentation of bearing-only tracking algorithms
    • Abstract: Publication date: Available online 11 October 2018Source: Annual Reviews in ControlAuthor(s): Riccardo Costanzi, Davide Fenucci, Vincenzo Manzari, Andrea Caiti, Roberto Petroccia Underwater navigation performance of Autonomous Underwater Vehicles (AUVs) strongly affects the quality of the collected data. Scientific literature extensively addresses the AUV tracking and self-localisation problems. However, no standard evaluation methods for vehicle navigation exist. Therefore, the authors’ visionary perspective is to develop and implement an Underwater Test Range (UTR) to certify the vehicle compliance with long-term underwater navigation. This paper describes a first step along this research path represented by an in field validation of such conceived measurement network. Experiments are soundly based on extensive simulation analysis presented in previous works. In particular, an underwater network composed of acoustic modems with Ultra Short BaseLine capabilities is deployed as measurement rig. This setup, through bearing-only measurements, allows the tracking of an Autonomous Surface Vehicle (ASV) equipped with Differential GPS as position ground truth. Results show how the proposed methodology performs in a real marine scenario with challenging conditions due to shallow waters and magnetically noisy environment.
  • A survey on control theory applications to operational systems, supply
           chain management, and Industry 4.0
    • Abstract: Publication date: Available online 11 October 2018Source: Annual Reviews in ControlAuthor(s): Dmitry Ivanov, Suresh Sethi, Alexandre Dolgui, Boris Sokolov Modern production and logistics systems, supply chains, and Industry 4.0 networks are challenged by increased uncertainty and risks, multiple feedback cycles, and dynamics. Control theory is an interesting research avenue which contributes to further insights concerning the management of the given challenges in operations and supply chain management. In this paper, the applicability of control theory to engineering and management problems in supply chain operations is investigated. Our analysis bridges the fundamentals of control and systems theory to supply chain and operations management. This study extends our previous survey in the Annual Reviews in Control (Ivanov et al. 2012) by including new literature published in 2012–2018, identifying two new directions of control theory applications (i.e., ripple effect analysis in the supply chains and scheduling in Industry 4.0) and analysis towards the digital technology use in control theoretic models. It describes important issues and perspectives that delineate dynamics in supply chains, operations, and Industry 4.0 networks and identifies and systemizes different streams in the application of control theory to operations and supply chain management and engineering in the period from 1960–2018. It updates the existing applications and classifications, performs a critical analysis, and discusses further research avenues. Further development of interdisciplinary approaches to supply chain optimization is argued. An extended cooperation between control engineers and supply chain experts may have the potential to introduce more realism to dynamic planning and models, and improve performance in production and logistics systems, supply chains, and Industry 4.0 networks. Finally, we analyze the trends towards the intellectualization of control and its development towards supply chain control analytics.
  • Small-gain theory for stability and control of dynamical networks: A
    • Abstract: Publication date: Available online 10 October 2018Source: Annual Reviews in ControlAuthor(s): Zhong-Ping Jiang, Tengfei Liu This paper provides a personal account of the small-gain theory as a tool for stability analysis, control synthesis, and robustness analysis for interconnected uncertain systems. A milestone in modern control theory is the development of a transformative stability criterion known as the classical small-gain theorem proposed by George Zames in 1966, that surpasses Lyapunov theory in that there is no need to construct Lyapunov functions for the finite-gain stability of feedback systems. Under the small-gain framework, a feedback system composed of two finite-gain stable subsystems remains finite-gain stable if the loop gain is less than one. Despite its apparent simplicity at first sight, Zames’s small-gain theorem plays a crucial role in the development of linear robust control theory. Borrowing techniques in modern nonlinear control, especially Sontag’s notion of input-to-state stability (ISS), the first generalized, nonlinear ISS small-gain theorem proposed by one of the authors in 1994 overcomes the two shortcomings of Zames’s small-gain theorem. First, the use of nonlinear gains allows to consider strongly nonlinear, interconnected systems. Second, the role of initial conditions is made explicit so that both internal Lyapunov stability and external input-output stability can be studied in a unified framework. In this survey paper, we first review early developments in the nonlinear small-gain theory for interconnected systems of various types such as continuous-time systems, discrete-time systems, hybrid systems and time-delay systems, along with applications in robust nonlinear control. Then, we describe how to obtain a network small-gain theory for large-scale dynamical networks that are comprised of more than two interacting nonlinear systems. Constructive methods for the generation of Lyapunov functions for the total network are presented as well. Finally, this paper discusses how the network/nonlinear small-gain theory can be applied to obtain innovative solutions to quantized and event-based nonlinear control problems, that are important for the development of a complete theory of controlling cyber-physical systems subject to communications and computation constraints.
  • A side-scan sonar data-driven coverage planning and tracking framework
    • Abstract: Publication date: Available online 10 October 2018Source: Annual Reviews in ControlAuthor(s): Nadir Kapetanović, Nikola Mišković, Adnan Tahirović, Marco Bibuli, Massimo Caccia Mapping an unknown large-scale marine area by a side-scan sonar onboard a marine vehicle as quickly as possible is often of great importance. It is also important that a-priori unknown interesting parts of the area are scanned in more detail, i.e. with the removal of sonic shadows. In contrast to the standard overlap-all-sonar-ranges lawnmower pattern offline static coverage problem solution for side-scan sonar missions, here a novel online side-scan sonar data-driven coverage solution is proposed. The proposed coverage algorithm provides a coverage solution based on local information gain from side-scan sonar data. At the same time, the solution is generated in such a way that coverage path length/time is minimized while covering the same area as the standard lawnmower. Upper and lower bounds of the proposed algorithm’s improvement compared to the overlap-all-sonar-ranges lawnmower method are estimated analytically and validated through extensive mission parameters variation simulations. Simulation results show that this approach can cut down coverage path length/time significantly compared to the standard lawnmower method in most application cases.
  • A robust interaction control approach for underwater vehicle manipulator
    • Abstract: Publication date: Available online 10 October 2018Source: Annual Reviews in ControlAuthor(s): Shahab Heshmati-Alamdari, Charalampos P. Bechlioulis, George C. Karras, Alexandros Nikou, Dimos V. Dimarogonas, Kostas J. Kyriakopoulos In underwater robotic interaction tasks (e.g., sampling of sea organisms, underwater welding, panel handling, etc) various issues regarding the uncertainties and complexity of the robot dynamic model, the external disturbances (e.g., sea currents), the steady state performance as well as the overshooting/undershooting of the interaction force error, should be addressed during the control design. Motivated by the aforementioned considerations, this paper presents a force/position tracking control protocol for an Underwater Vehicle Manipulator System (UVMS) in compliant contact with a planar surface, without incorporating any knowledge of the UVMS dynamic model, the exogenous disturbances or the contact stiffness model. Moreover, the proposed control framework guarantees: (i) certain predefined minimum speed of response, maximum steady state error as well as overshoot/undershoot concerning the force/position tracking errors, (ii) contact maintenance and (iii) bounded closed loop signals. Additionally, the achieved transient and steady state performance is solely determined by certain designer-specified performance functions/parameters and is fully decoupled from the control gain selection and the initial conditions. Finally, both simulation and experimental studies clarify the proposed method and verify its efficiency.
  • Review and big data perspectives on robust data mining approaches for
           industrial process modeling with outliers and missing data
    • Abstract: Publication date: Available online 5 October 2018Source: Annual Reviews in ControlAuthor(s): Jinlin Zhu, Zhiqiang Ge, Zhihuan Song, Furong Gao Industrial process data are usually mixed with missing data and outliers which can greatly affect the statistical explanation abilities for traditional data-driven modeling methods. In this sense, more attention should be paid on robust data mining methods so as to investigate those stable and reliable modeling prototypes for decision-making. This paper gives a systematic review of various state-of-the-art data preprocessing tricks as well as robust principal component analysis methods for process understanding and monitoring applications. Afterwards, comprehensive robust techniques have been discussed for various circumstances with diverse process characteristics. Finally, big data perspectives on potential challenges and opportunities have been highlighted for future explorations in the community.
  • Structure assignment problems in linear systems: Algebraic and geometric
    • Abstract: Publication date: Available online 2 October 2018Source: Annual Reviews in ControlAuthor(s): Nicos Karcanias, John Leventides, Ioannis Meintanis The Determinantal Assignment Problem (DAP) is a family of synthesis methods that has emerged as the abstract formulation of pole, zero assignment of linear systems. This unifies the study of frequency assignment problems of multivariable systems under constant, dynamic centralized, or decentralized control structure. The DAP approach is relying on exterior algebra and introduces new system invariants of rational vector spaces, the Grassmann vectors and Plücker matrices. The approach can handle both generic and non-generic cases, provides solvability conditions, enables the structuring of decentralisation schemes using structural indicators and leads to a novel computational framework based on the technique of Global Linearisation. DAP introduces a new approach for the computation of exact solutions, as well as approximate solutions, when exact solutions do not exist using new results for the solution of exterior equations. The paper provides a review of the tools, concepts and results of the DAP framework and a research agenda based on open problems.
  • Advanced state estimation for navigation of automated vehicles
    • Abstract: Publication date: Available online 2 October 2018Source: Annual Reviews in ControlAuthor(s): Thomas Konrad, Jan-Jöran Gehrt, Jiaying Lin, René Zweigel, Dirk Abel For the emerging topic of automated and autonomous vehicles in all major sectors, reliable and accurate state estimation for navigation of these vehicles becomes increasingly important. Inertial navigation, aided with measurements from global navigation satellite systems (GNSS), allows high-rate and low-cost estimation of position, velocity and orientation in real-time applications. As the available satellite constellations for navigation are modernized and their number is rising, usage of multi-constellation, dual-frequency and integration of correction data lead to increased accuracy, especially in areas with partial shadowing. Different coupling methods, e.g. tightly- and loosely-coupled integrations, were developed to combine inertial and GNSS measurements. Also different error estimation filters were applied to the navigation problem, and evaluated against each other. For the typical navigation task, the objective is to choose a suitable algorithm for the specific requirements of the target application, and deploy it using an appropriate implementation strategy. This contribution gives a short introduction into the field of aided inertial navigation techniques, provides useful hints for implementation, and evaluates their performance in experiments using two different railway vehicles, an autonomous maritime vessel, and an unmanned aerial quadrotor.
  • Robot ecology: Constraint-based control design for long duration autonomy
    • Abstract: Publication date: Available online 30 September 2018Source: Annual Reviews in ControlAuthor(s): Magnus Egerstedt, Jonathan N. Pauli, Gennaro Notomista, Seth Hutchinson Long duration autonomy considers robots that are deployed over long time scales. As a result, the robots’ ability to operate across changing environmental conditions and perform tasks that require more time to complete than what can be supported on a single battery charge, have implications for how the control design task should be approached. By drawing inspiration from ecology, which concerns itself with the strong coupling between organism and the environment it inhabits, we encode these “survival constraints” through Boolean compositions of multiple control barrier functions, and show how this construction supports long duration autonomy in the context of persistent environmental monitoring on a team of mobile robots.
  • A review on damping of torsional interactions using VSC based FACTS and
           subsynchronous damping controller
    • Abstract: Publication date: Available online 31 August 2018Source: Annual Reviews in ControlAuthor(s): S. Venkateswarlu, M. Janaki, R. Thirumalaivasan, Nagesh Prabhu Improvement in the power transfer capability and the system stability of long transmission lines by series compensation is a cost-effective solution. However, the Subsynchronous Resonance (SSR) due to series compensation leads to severe risk of Torsional Interactions (TI). This paper presents, a review on damping of torsional interactions using Voltage Source Converter (VSC) based FACTS with various Subsynchronous Damping Controllers (SSDC) proposed in the literature. This review can help researchers to make a comparative study of the impact of FACTS devices and various subsynchronous damping controllers on damping of subsynchronous oscillations.
  • Current advancements on autonomous mission planning and management
           systems: An AUV and UAV perspective
    • Abstract: Publication date: Available online 7 August 2018Source: Annual Reviews in ControlAuthor(s): Adham Atyabi, Somaiyeh MahmoudZadeh, Samia Nefti-Meziani Advances in hardware technology have enabled more integration of sophisticated software, triggering progresses in development and employment of Unmanned Vehicles (UVs), and mitigating restraints for onboard intelligence. As a result, UVs can now take part in more complex mission where continuous transformation in environmental condition calls for higher level of situational responsiveness. This paper serves as an introduction to UVs mission planning and management systems aiming to highlight some of the recent developments in the field of autonomous underwater and aerial vehicles in addition to stressing some possible future directions and discussing the learned lessons. A comprehensive survey over autonomy assessment of UVs, and different aspects of autonomy such as situation awareness, cognition, and decision-making has been provided in this study. The paper separately explains the humanoid and autonomous system's performance and highlights the role and impact of a human in UVs operations.
  • Dealing with observational data in control
    • Abstract: Publication date: Available online 29 May 2018Source: Annual Reviews in ControlAuthor(s): Emma D. Wilson, Quentin Clairon, Robin Henderson, C. James Taylor There is growing interest in the use of control theory for interdisciplinary applications, where data may be sparse or missing, be non-uniformly sampled, have greater uncertainty, and where there is no opportunity to collect repeat measurements. In such applications, problems posed by observational data and the issue of missing or irregular data need to be considered. We present a review on dealing with observational, missing and irregular data for control applications. This considers the following issues: (i) how to identify a system model from observational data subject to missing measurements, (ii) how to determine control inputs when output data includes missing measurements, and (iii) how to ensure stability when future update times may be missed. Dealing with observational data and missing measurements is a key problem within the statistics literature, so we introduce statistical methods for dealing with this type of data. We aim to enable the integration of well-developed statistical methods of dealing with missing data into control theory. An example problem of using anticoagulants to control the blood clotting speed of patients is used throughout the paper.
  • Perturbation analysis: A framework for data-driven control and
           optimization of discrete event and hybrid systems
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Y. Wardi, C.G. Cassandras, X.R. Cao The history of Perturbation Analysis (PA) is intimately related to that of Discrete Event Dynamic Systems (DEDS), starting with a solution of a long-standing problem in the late 1970s and continuing today with the control and optimization of Hybrid Systems and the emergence of event-driven control methods. We review the origins of the PA theory and how it became part of a broader framework for modelling, control and optimization of DEDS. We then discuss the theoretical underpinnings of Infinitesimal Perturbation Analysis (IPA) as a data-driven stochastic gradient estimation method and how it has been applied over the past few decades. We explain how IPA offers a basis for general-purpose stochastic optimization of Markovian systems through the notion of the performance potential and how it has evolved beyond DEDS and now provides a framework for control and optimization of Hybrid Systems and, more generally, event-driven methodologies.
  • Max-plus algebra in the history of discrete event systems
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): J. Komenda, S. Lahaye, J.-L. Boimond, T. van den Boom This paper is a survey of the history of max-plus algebra and its role in the field of discrete event systems during the last three decades. It is based on the perspective of the authors but it covers a large variety of topics, where max-plus algebra plays a key role.
  • Petri nets and Automatic Control: A historical perspective
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Alessandro Giua, Manuel Silva The goal of this paper is to overview the historical development of the field of Petri nets (PNs) from a Systems Theory and Automatic Control perspective. It is intentionally not meant to be comprehensive: we limit ourselves to outline, through selected representative topics, some of the conceptual issues studied in the literature. In a first part we retrace the emergence of some basic net concepts to provide a broad view of the family of PN formalisms. Then we focus, more specifically, on the use of Petri nets within Automatic Control. Discrete net models have been considered since the middle of the 70s and starting since the late 80s have also been used for addressing classical problems, such as supervisory and deadlock control, state estimation, diagnosis, and so on. The double benefit is the ability to model a larger class of systems and to provide efficient algorithms for solving certain of those problems. We also discuss new approaches based on continuous and hybrid nets, which have been developed within the Automatic Control community.
  • On the history of Discrete Event Systems
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Manuel Silva The purpose of this article is to provide a viewpoint of the development of the field of Discrete Event Systems (DES). Necessarily incomplete, because of the breath of topics and richness of research results, this paper is mainly presented from a System Theory-Automatic Control (AC) perspective. Written with a certain emphasis at the dawn of the discipline, the following five articles of this special section of the journal provide essential complements on its evolution along the four last decades. Starting with the identification of three basic threads along which many developments took place, the multidisciplinary and dynamic character of DES and the diversity of formalisms and techniques that are used are stressed.
  • Special section on the history of Discrete Event Systems
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Manuel Silva
  • Rudolf E. Kalman’s quest for algebraic characterizations of
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Tryphon T. Georgiou The present paper is a tribute to Professor Rudolf Emil Kalman, father of Mathematical System Theory and a towering figure in the field of Control and Dynamical Systems. Amongst his seminal contributions was a series of results and insights into the role of positivity in System Theory and in Control Engineering. The paper contains a collection of reminiscences by the author together with brief technical references that touch upon the unparalleled influence of Professor Kalman on this topic.
  • A framework for receding-horizon control in infinite-horizon aggregative
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Filiberto Fele, Antonio De Paola, David Angeli, Goran Strbac A novel modelling framework is proposed for the analysis of aggregative games on an infinite-time horizon, assuming that players are subject to heterogeneous periodic constraints. A new aggregative equilibrium notion is presented and the strategic behaviour of the agents is analysed under a receding horizon paradigm. The evolution of the strategies predicted and implemented by the players over time is modelled through a discrete-time multi-valued dynamical system. By considering Lyapunov stability notions and applying limit and invariance results for set-valued correspondences, necessary conditions are derived for convergence of a receding horizon map to a periodic equilibrium of the aggregative game. This result is achieved for any (feasible) initial condition, thus ensuring implicit adaptivity of the proposed control framework to real-time variations in the number and parameters of players. Design and implementation of the proposed control strategy are discussed and an example of distributed control for data routing is presented, evaluating its performance in simulation.
  • Comparative performances of synchronisation between different classes of
           chaotic systems using three control techniques
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): P.P. Singh, B.K. Roy This paper puts forward the comparative performances for synchronisation between (i) systems from different chaotic system families, (ii) systems from the Unified Chaotic System (UCS) family, (iii) a hyperchaotic and a chaotic systems and (iv) identical chaotic systems. Three different well-known control techniques, i.e. Nonlinear Active Control (NAC), Sliding Mode Control (SMC) and Adaptive Control (AC) are used for synchronisation between various pairs of chaotic and/or hyperchaotic systems. Performances of NAC, SMC and AC techniques are investigated and compared with synchronisation of different pairs of chaotic systems based on the error dynamics and required control inputs. The integral square error and required control energy measures are considered for comparison. Finally, a generalised view on the use of the control techniques for synchronisation is finally proposed. Moreover, a new chaotic system is proposed and its qualitative analysis is done to illustrate the chaotic behaviour of the system. The new system is used as an example of synchronisation. MATLAB simulation results are presented which reflect the successful achievement of the objectives.
  • Microgrid control: A comprehensive survey
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Sachidananda Sen, Vishal Kumar Present researches in power and energy fraternity are driven towards the realization of smart grid (SG) technologies. Microgrids (MGs) being regarded as “elementary units” of SG, has undergone rigorous research for more than one and a half decade now. It provides an integration platform for microsources (MSs), loads, storage devices and power electronics (PE) converters at demand premises forming a system of systems i.e. SoSs architecture. MGs mostly operated in grid-tied mode but during an emergency, are capable of standalone operation. Stability and operational control during both the modes are of utmost concern. Involvement of several control functionalities viz. normalcy of voltage and frequency, optimal power sharing, islanding detection etc., had been adhered in the literature. In spite of that, the real world implementation has not been of significant extent, that too even is far from having ideal MG characteristics, eligible for commercial usage. These technical obstacles need to be identified and dealt with. This paper provides a comprehensive survey of different control aspects of MGs, broadly classified under four control strategies: centralized, decentralized, distributed and hierarchical frameworks. Each scheme is reviewed in detail w.r.t the principles behind, their applicability and performances. It also identifies several research gaps and future trends therein. The technical barriers for real scale application and their solutions are also briefly discussed. And finally, a discussion on different integrated technologies for MGs, to realize SG features is also presented.
  • Stochastic model predictive control with active uncertainty learning: A
           Survey on dual control
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Ali Mesbah This paper provides a review of model predictive control (MPC) methods with active uncertainty learning. System uncertainty poses a key theoretical and practical challenge in MPC, which can be aggravated when system uncertainty increases due to the time-varying nature of system dynamics. For uncertain systems with stochastic uncertainty, this paper presents the stochastic MPC (SMPC) problem in the dual control paradigm, where the control inputs to an uncertain system have a probing effect for active uncertainty learning and a directing effect for controlling the system dynamics. The complexity of the SMPC problem with dual control effect is described in connection to stochastic dynamic programming as well as Bayesian estimation for its output feedback implementation. Further, implicit and explicit dual control methods for approximating the receding-horizon control problem with dual control effect are surveyed and analyzed with the intent to discuss the key challenges and opportunities in SMPC with dual control effect.
  • A survey on the analysis and control of evolutionary matrix games
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): James Riehl, Pouria Ramazi, Ming Cao In support of the growing interest in how to efficiently influence complex systems of interacting self-interested agents, we present this review of fundamental concepts, emerging research, and open problems related to the analysis and control of evolutionary matrix games, with particular emphasis on applications in social, economic, and biological networks.
  • Trajectory planning and tracking for autonomous overtaking:
           State-of-the-art and future prospects
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Shilp Dixit, Saber Fallah, Umberto Montanaro, Mehrdad Dianati, Alan Stevens, Francis Mccullough, Alexandros Mouzakitis Trajectory planning and trajectory tracking constitute two important functions of an autonomous overtaking system and a variety of strategies have been proposed in the literature for both functionalities. However, uncertainties in environment perception using the current generation of sensors has resulted in most proposed methods being applicable only during low-speed overtaking. In this paper, trajectory planning and trajectory tracking approaches for autonomous overtaking systems are reviewed. The trajectory planning techniques are compared based on aspects such as real-time implementation, computational requirements, and feasibility in real-world scenarios. This review shows that two important aspects of trajectory planning for high-speed overtaking are: (i) inclusion of vehicle dynamics and environmental constraints and (ii) accurate knowledge of the environment and surrounding obstacles. The review of trajectory tracking controllers for high-speed driving is based on different categories of control algorithms where their respective advantages and disadvantages are analysed. This study shows that while advanced control methods improve tracking performance, in most cases the results are valid only within well-regulated conditions. Therefore, existing autonomous overtaking solutions assume precise knowledge of surrounding environment which is not representative of real-world driving. The paper also discusses how in a connected driving environment, vehicles can access additional information that can expand their perception. Hence, the potential of cooperative information sharing for aiding autonomous high-speed overtaking manoeuvre is identified as a possible solution.
  • Multi-layered interactive energy space modeling for near-optimal
           electrification of terrestrial, shipboard and aircraft systems
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Marija D. Ilić, Rupamathi Jaddivada In this paper, we introduce a basic multi-layered modeling framework for posing the problem of safe, robust and efficient design and control that may lend itself to ripping potential benefits from electrification. The proposed framework establishes dynamic relations between physical concepts such as stored energy, useful work, and wasted energy, on one hand; and modeling, simulation, and control of interactive modular complex dynamical systems, on the other. In particular, our recently introduced energy state-space modeling approach for electric energy systems is further interpreted using fundamental laws of physics in multi-physical systems, such as terrestrial energy-systems, aircrafts and ships. The interconnected systems are modeled as dynamically interacting modules. This approach is shown to be particularly well-suited for scalable optimization of large-scale complex systems. Instead of having to use simpler models, the proposed multi-layered modeling of system dynamics in energy space offers a promising basic method for modeling and controlling inter-dependencies across multi-physics subsystems for both ensuring feasible and near-optimal operation. It is illustrated how this approach can be used for understanding fundamental physical causes of inefficiencies created either at the component level or are a result of poor matching of their interactions.
  • On flight operational issues management: Past, present and future
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Ali Zolghadri This paper provides a brief perspective of academic model-based Fault Detection, Identification and Recovery (FDIR) developments for aerospace and flight systems, and discusses a future paradigm shift in civil aviation operations.
  • Control of connected and automated vehicles: State of the art and future
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Jacopo Guanetti, Yeojun Kim, Francesco Borrelli Autonomous driving technology pledges safety, convenience, and energy efficiency. Its challenges include the unknown intentions of other road users: communication between vehicles and with the road infrastructure is a possible approach to enhance awareness and enable cooperation. Connected and automated vehicles (CAVs) have the potential to disrupt mobility, extending what is possible with driving automation and connectivity alone. Applications include real-time control and planning with increased awareness, routing with micro-scale traffic information, coordinated platooning using traffic signals information, and eco-mobility on demand with guaranteed parking. This paper introduces a control and planning architecture for CAVs, and surveys the state of the art on each functional block therein; the main focus is on techniques to improve energy efficiency. We provide an overview of existing algorithms and their mutual interactions, we present promising optimization-based approaches to CAVs control and identify future challenges.
  • Future systems and control research in synthetic biology
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Domitilla Del Vecchio, Yili Qian, Richard M. Murray, Eduardo D. Sontag Synthetic biology is the application of engineering principles to the fundamental components of biology, with the aim of creating systems with novel functionalities that can be used for energy, environment, and medical applications. While the potential impact of this new technology is enormous, there are challenges that we need to overcome before the impact of synthetic biology can be fully realized. Many of these challenges fall beyond the scope of molecular biology and are indeed “system-level” problems, where very little research is being performed. This paper identifies pressing challenges in synthetic biology that can be formulated as systems and control theoretic problems and outlines potentially new systems and control theories/tools that are required to tackle such problems. The aim is to attract more systems and control theorists to collaborate with molecular biologists and biophysicists and help synthetic biology reach its promise. At the same time, engaging the systems and control community more broadly into the rich research opportunities and life-changing applications of synthetic biology may provide added visibility to the field of systems and controls.
  • Advancing systems and control research in the era of ML and AI
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Pramod P. Khargonekar, Munther A. Dahleh Fields of machine learning and artificial intelligence are undergoing transformative advances and growth. This article presents a vision for the field of systems and control that simultaneously leverages these advances to more fully engage with them and spur new expansive research directions in systems and control.
  • On the history of diagnosability and opacity in discrete event systems
    • Abstract: Publication date: 2018Source: Annual Reviews in Control, Volume 45Author(s): Stéphane Lafortune, Feng Lin, Christoforos N. Hadjicostis This paper presents historical remarks on key projects and papers that led to the development of a theory of event diagnosis for discrete event systems modeled by finite-state automata or Petri nets in the 1990s. The goal in event diagnosis is to develop algorithmic procedures for deducing the occurrence of unobservable events, based on a formal model of the system and on-line observations of its behavior. It also presents historical remarks on the early works on the property of opacity, which occurred about ten years later. Opacity can be seen as a strong version of lack of diagnosability and it has been used to capture security and privacy requirements. Finally, diagnosability is connected with the property of observability that arises in supervisory control. This paper is part of set of papers that review the emergence of discrete event systems as an area of research in control engineering.
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Heriot-Watt University
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