Learning Control
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Iterative Learning Control For Multi Agent Systems Coordination
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Author : Shiping Yang
language : en
Publisher: John Wiley & Sons
Release Date : 2017-03-03
Iterative Learning Control For Multi Agent Systems Coordination written by Shiping Yang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-03 with Technology & Engineering categories.
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
Machine Learning Control Taming Nonlinear Dynamics And Turbulence
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Author : Thomas Duriez
language : en
Publisher: Springer
Release Date : 2016-11-02
Machine Learning Control Taming Nonlinear Dynamics And Turbulence written by Thomas Duriez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-02 with Technology & Engineering categories.
This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail. Experimental control demonstrations from a laminar shear-layer to turbulent boundary-layers are reviewed in Chapter 6, followed by general good practices for experiments in Chapter 7. The book concludes with an outlook on the vast future applications of MLC in Chapter 8. Matlab codes are provided for easy reproducibility of the presented results. The book includes interviews with leading researchers in turbulence control (S. Bagheri, B. Batten, M. Glauser, D. Williams) and machine learning (M. Schoenauer) for a broader perspective. All chapters have exercises and supplemental videos will be available through YouTube.
Iterative Learning Control For Systems With Iteration Varying Trial Lengths
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Author : Dong Shen
language : en
Publisher: Springer
Release Date : 2019-01-29
Iterative Learning Control For Systems With Iteration Varying Trial Lengths written by Dong Shen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Technology & Engineering categories.
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 numerousintuitive 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.
Intelligent Control Principles Techniques And Applications
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Author : Zixing Cai
language : en
Publisher: World Scientific
Release Date : 1997-12-18
Intelligent Control Principles Techniques And Applications written by Zixing Cai and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-12-18 with Technology & Engineering categories.
This book introduces the development process, structural theories and research areas of intelligent control; explains the knowledge representations, searching and reasoning mechanisms as the fundamental techniques of intelligent control; studies the theoretical principles and architectures of various intelligent control systems; analyzes the paradigms of representative applications of intelligent control; and discusses the research and development trends of the intelligent control.From the general point of view, this book possesses the following features: updated research results both in theory and application that reflect the latest advances in intelligent control; closed connection between theory and practice that enables readers to use the principles to their case studies and practical projects; and comprehensive materials that helps readers in understanding and learning.
Iterative Learning Control For Network Systems Under Constrained Information Communication
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Author : Wenjun Xiong
language : en
Publisher: Springer Nature
Release Date : 2024-03-26
Iterative Learning Control For Network Systems Under Constrained Information Communication written by Wenjun Xiong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-26 with Technology & Engineering categories.
This book focuses on the subject area of Network Systems and Control Theory, providing a comprehensive examination of the dynamic behavior of networked systems operating under communication constraints. It introduces innovative iterative learning control strategies that aim to ensure stability, consistency, and security of networked systems. The field of networked systems has garnered significant interest from scientists and engineers across various disciplines, including information, electrical, transportation, life, social, and management sciences. This book consistently addresses a wide range of issues related to networked systems, emphasizing the critical impact of communication constraints on stability and security. It highlights the effectiveness and importance of iterative learning methods in tackling these challenges. Suitable for both undergraduate and graduate students interested in networked systems and iterative learning control, this book alsoserves as a valuable resource for university faculty and engineers engaged in complex systems, control theory research, and real-world applications. Its broad appeal extends to professionals working in related fields, seeking a deeper understanding of networked systems and their control mechanisms.
Automation And Control
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Author : Constantin Volosencu
language : en
Publisher: BoD – Books on Demand
Release Date : 2021-04-21
Automation And Control written by Constantin Volosencu and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-21 with Technology & Engineering categories.
The book presents recent theoretical and practical information about the field of automation and control. It includes fifteen chapters that promote automation and control in practical applications in the following thematic areas: control theory, autonomous vehicles, mechatronics, digital image processing, electrical grids, artificial intelligence, and electric motor drives. The book also presents and discusses applications that improve the properties and performances of process control with examples and case studies obtained from real-world research in the field. Automation and Control is designed for specialists, engineers, professors, and students.
Data Driven Iterative Learning Control For Discrete Time Systems
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Author : Ronghu Chi
language : en
Publisher: Springer Nature
Release Date : 2022-11-15
Data Driven Iterative Learning Control For Discrete Time Systems written by Ronghu Chi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-15 with Technology & Engineering categories.
This book belongs to the subject of control and systems theory. It studies a novel data-driven framework for the design and analysis of iterative learning control (ILC) for nonlinear discrete-time systems. A series of iterative dynamic linearization methods is discussed firstly to build a linear data mapping with respect of the system’s output and input between two consecutive iterations. On this basis, this work presents a series of data-driven ILC (DDILC) approaches with rigorous analysis. After that, this work also conducts significant extensions to the cases with incomplete data information, specified point tracking, higher order law, system constraint, nonrepetitive uncertainty, and event-triggered strategy to facilitate the real applications. The readers can learn the recent progress on DDILC for complex systems in practical applications. This book is intended for academic scholars, engineers, and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.
Iterative Learning Control
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Author : Zeungnam Bien
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Iterative Learning Control written by Zeungnam Bien and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
Iterative Learning Control (ILC) differs from most existing control methods in the sense that, it exploits every possibility to incorporate past control informa tion, such as tracking errors and control input signals, into the construction of the present control action. There are two phases in Iterative Learning Control: first the long term memory components are used to store past control infor mation, then the stored control information is fused in a certain manner so as to ensure that the system meets control specifications such as convergence, robustness, etc. It is worth pointing out that, those control specifications may not be easily satisfied by other control methods as they require more prior knowledge of the process in the stage of the controller design. ILC requires much less information of the system variations to yield the desired dynamic be haviors. Due to its simplicity and effectiveness, ILC has received considerable attention and applications in many areas for the past one and half decades. Most contributions have been focused on developing new ILC algorithms with property analysis. Since 1992, the research in ILC has progressed by leaps and bounds. On one hand, substantial work has been conducted and reported in the core area of developing and analyzing new ILC algorithms. On the other hand, researchers have realized that integration of ILC with other control techniques may give rise to better controllers that exhibit desired performance which is impossible by any individual approach.
Variable Gain Design In Stochastic Iterative Learning Control
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Author : Dong Shen
language : en
Publisher: Springer Nature
Release Date : 2025-01-02
Variable Gain Design In Stochastic Iterative Learning Control written by Dong Shen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-02 with Technology & Engineering categories.
This book investigates the critical gain design in stochastic iterative learning control (SILC), including four specific gain design strategies: decreasing gain design, adaptive gain design, event-triggering gain design, and optimal gain design. The key concept for the gain design is to balance multiple performance indices such as high tracking precision, effective noise reduction, and fast convergence speed. These gain design techniques can be applied to various control algorithms for stochastic systems to realize a high tracking performance. This book provides a series of design and analysis techniques for the establishment of a systematic framework of gain design in SILC. The book is intended for scholars and graduate students who are interested in stochastic control, recursive algorithms design, and iterative learning control.
Iterative Learning Control With Passive Incomplete Information
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Author : Dong Shen
language : en
Publisher: Springer
Release Date : 2018-04-16
Iterative Learning Control With Passive Incomplete Information written by Dong Shen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-16 with Technology & Engineering categories.
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.