Iterative Learning Control for Network Systems Under Constrained Information Communication
Author: Wenjun Xiong
Publisher: Springer Nature
Published:
Total Pages: 229
ISBN-13: 9819709261
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Iterative Learning Control with Passive Incomplete Information
Author: Dong Shen
Publisher:
Published: 2018
Total Pages:
ISBN-13: 9789811082689
DOWNLOAD EBOOK →This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.--a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model--for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields.
Iterative Learning Control for Multi-agent Systems Coordination
Author: Shiping Yang
Publisher: John Wiley & Sons
Published: 2017-03-03
Total Pages: 260
ISBN-13: 1119189063
DOWNLOAD EBOOK →A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, showcasing recent advances and industrially relevant applications Explores the synergy between the important topics of iterative learning control (ILC) and multi-agent systems (MAS) Concisely summarizes recent advances and significant applications in ILC methods for power grids, sensor networks and control processes Covers basic theory, rigorous mathematics as well as engineering practice
Iterative Learning Control for Systems with Iteration-Varying Trial Lengths
Author: Dong Shen
Publisher: Springer
Published: 2019-01-29
Total Pages: 256
ISBN-13: 9811361363
DOWNLOAD EBOOK →This book presents a comprehensive and detailed study on iterative learning control (ILC) for systems with iteration-varying trial lengths. Instead of traditional ILC, which requires systems to repeat on a fixed time interval, this book focuses on a more practical case where the trial length might randomly vary from iteration to iteration. The iteration-varying trial lengths may be different from the desired trial length, which can cause redundancy or dropouts of control information in ILC, making ILC design a challenging problem. The book focuses on the synthesis and analysis of ILC for both linear and nonlinear systems with iteration-varying trial lengths, and proposes various novel techniques to deal with the precise tracking problem under non-repeatable trial lengths, such as moving window, switching system, and searching-based moving average operator. It not only discusses recent advances in ILC for systems with iteration-varying trial lengths, but also includes numerous intuitive figures to allow readers to develop an in-depth understanding of the intrinsic relationship between the incomplete information environment and the essential tracking performance. This book is intended for academic scholars and engineers who are interested in learning about control, data-driven control, networked control systems, and related fields. It is also a useful resource for graduate students in the above field.
Iterative Learning Control for Multi-agent Systems Coordination
Author: Shiping Yang
Publisher: John Wiley & Sons
Published: 2017-03-08
Total Pages: 408
ISBN-13: 1119189071
DOWNLOAD EBOOK →A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, showcasing recent advances and industrially relevant applications Explores the synergy between the important topics of iterative learning control (ILC) and multi-agent systems (MAS) Concisely summarizes recent advances and significant applications in ILC methods for power grids, sensor networks and control processes Covers basic theory, rigorous mathematics as well as engineering practice
Networked Predictive Control of Systems with Communication Constraints and Cyber Attacks
Author: Zhong-Hua Pang
Publisher: Springer
Published: 2018-06-12
Total Pages: 219
ISBN-13: 981130520X
DOWNLOAD EBOOK →This book presents the latest results on predictive control of networked systems, where communication constraints (e.g., network-induced delays and packet dropouts) and cyber attacks (e.g., deception attacks and denial-of-service attacks) are considered. For the former, it proposes several networked predictive control (NPC) methods based on input-output models and state-space models respectively. For the latter, it designs secure NPC schemes from the perspectives of information security and real-time control. Furthermore, it uses practical experiments to demonstrate the effectiveness and applicability of all the methods, bridging the gap between control theory and practical applications. The book is of interest to academic researchers, R&D engineers, and graduate students in control engineering, networked control systems and cyber-physical systems.
Iterative Learning Control with Passive Incomplete Information
Author: Dong Shen
Publisher: Springer
Published: 2018-04-16
Total Pages: 294
ISBN-13: 9811082677
DOWNLOAD EBOOK →This book presents an in-depth discussion of iterative learning control (ILC) with passive incomplete information, highlighting the incomplete input and output data resulting from practical factors such as data dropout, transmission disorder, communication delay, etc.—a cutting-edge topic in connection with the practical applications of ILC. It describes in detail three data dropout models: the random sequence model, Bernoulli variable model, and Markov chain model—for both linear and nonlinear stochastic systems. Further, it proposes and analyzes two major compensation algorithms for the incomplete data, namely, the intermittent update algorithm and successive update algorithm. Incomplete information environments include random data dropout, random communication delay, random iteration-varying lengths, and other communication constraints. With numerous intuitive figures to make the content more accessible, the book explores several potential solutions to this topic, ensuring that readers are not only introduced to the latest advances in ILC for systems with random factors, but also gain an in-depth understanding of the intrinsic relationship between incomplete information environments and essential tracking performance. It is a valuable resource for academics and engineers, as well as graduate students who are interested in learning about control, data-driven control, networked control systems, and related fields.
Recursive Filtering for 2-D Shift-Varying Systems with Communication Constraints
Author: Jinling Liang
Publisher: CRC Press
Published: 2021-09-06
Total Pages: 152
ISBN-13: 100042930X
DOWNLOAD EBOOK →This book presents up-to-date research developments and novel methodologies regarding recursive filtering for 2-D shift-varying systems with various communication constraints. It investigates recursive filter/estimator design and performance analysis by a combination of intensive stochastic analysis, recursive Riccati-like equations, variance-constrained approach, and mathematical induction. Each chapter considers dynamics of the system, subtle design of filter gains, and effects of the communication constraints on filtering performance. Effectiveness of the derived theories and applicability of the developed filtering strategies are illustrated via simulation examples and practical insight. Features:- Covers recent advances of recursive filtering for 2-D shift-varying systems subjected to communication constraints from the engineering perspective. Includes the recursive filter design, resilience operation and performance analysis for the considered 2-D shift-varying systems. Captures the essence of the design for 2-D recursive filters. Develops a series of latest results about the robust Kalman filtering and protocol-based filtering. Analyzes recursive filter design and filtering performance for the considered systems. This book aims at graduate students and researchers in mechanical engineering, industrial engineering, communications networks, applied mathematics, robotics and control systems.
Frontiers Of Intelligent Control And Information Processing
Author: Derong Liu
Publisher: World Scientific
Published: 2014-08-13
Total Pages: 480
ISBN-13: 9814616893
DOWNLOAD EBOOK →The current research and development in intelligent control and information processing have been driven increasingly by advancements made from fields outside the traditional control areas, into new frontiers of intelligent control and information processing so as to deal with ever more complex systems with ever growing size of data and complexity.As researches in intelligent control and information processing are taking on ever more complex problems, the control system as a nuclear to coordinate the activity within a system increasingly need to be equipped with the capability to analyze, and reason so as to make decision. This requires the support of cognitive components, and communication protocol to synchronize events within the system to operate in unison.In this review volume, we invited several well-known experts and active researchers from adaptive/approximate dynamic programming, reinforcement learning, machine learning, neural optimal control, networked systems, and cyber-physical systems, online concept drift detection, pattern recognition, to contribute their most recent achievements into the development of intelligent control systems, to share with the readers, how these inclusions helps to enhance the cognitive capability of future control systems in handling complex problems.This review volume encapsulates the state-of-art pioneering works in the development of intelligent control systems. Proposition and evocations of each solution is backed up with evidences from applications, could be used as references for the consideration of decision support and communication components required for today intelligent control systems.
Control and Scheduling Codesign
Author: Feng Xia
Publisher: Springer Science & Business Media
Published: 2008-10-11
Total Pages: 256
ISBN-13: 3540782559
DOWNLOAD EBOOK →With emphasis on flexible resource management in networked and embedded real-time control systems operating in dynamic environments with uncertainty, this book is devoted to the integration of control with computing and communication. It covers the authors' recent and original research results within a unified framework of feedback scheduling. This useful reference also includes rich example problems, case studies, and extensive references to the literature.
