Discrete Time Adaptive Iterative Learning Control
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Discrete Time Adaptive Iterative Learning Control
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Author : Ronghu Chi
language : en
Publisher: Springer Nature
Release Date : 2022-03-21
Discrete Time Adaptive Iterative Learning Control 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 2022-03-21 with Technology & Engineering categories.
This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various 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.
Adaptive Dynamic Programming Single And Multiple Controllers
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Author : Ruizhuo Song
language : en
Publisher: Springer
Release Date : 2018-12-28
Adaptive Dynamic Programming Single And Multiple Controllers written by Ruizhuo Song and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-28 with Technology & Engineering categories.
This book presents a class of novel optimal control methods and games schemes based on adaptive dynamic programming techniques. For systems with one control input, the ADP-based optimal control is designed for different objectives, while for systems with multi-players, the optimal control inputs are proposed based on games. In order to verify the effectiveness of the proposed methods, the book analyzes the properties of the adaptive dynamic programming methods, including convergence of the iterative value functions and the stability of the system under the iterative control laws. Further, to substantiate the mathematical analysis, it presents various application examples, which provide reference to real-world practices.
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 Algorithms And Experimental Benchmarking
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Author : Eric Rogers
language : en
Publisher: John Wiley & Sons
Release Date : 2023-01-12
Iterative Learning Control Algorithms And Experimental Benchmarking written by Eric Rogers 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 2023-01-12 with Technology & Engineering categories.
Iterative Learning CONTROL ALGORITHMS AND EXPERIMENTAL BENCHMARKING Iterative Learning Control Algorithms and Experimental Benchmarking Presents key cutting edge research into the use of iterative learning control The book discusses the main methods of iterative learning control (ILC) and its interactions, as well as comparator performance that is so crucial to the end user. The book provides integrated coverage of the major approaches to-date in terms of basic systems, theoretic properties, design algorithms, and experimentally measured performance, as well as the links with repetitive control and other related areas. Key features: Provides comprehensive coverage of the main approaches to ILC and their relative advantages and disadvantages. Presents the leading research in the field along with experimental benchmarking results. Demonstrates how this approach can extend out from engineering to other areas and, in particular, new research into its use in healthcare systems/rehabilitation robotics. The book is essential reading for researchers and graduate students in iterative learning control, repetitive control and, more generally, control systems theory and its applications.
Advances In Neural Networks Isnn 2007
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Author : Derong Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-24
Advances In Neural Networks Isnn 2007 written by Derong Liu 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 2007-05-24 with Computers categories.
Annotation The three volume set LNCS 4491/4492/4493 constitutes the refereed proceedings of the 4th International Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007. The 262 revised long papers and 192 revised short papers presented were carefully reviewed and selected from a total of 1.975 submissions. The papers are organized in topical sections on neural fuzzy control, neural networks for control applications, adaptive dynamic programming and reinforcement learning, neural networks for nonlinear systems modeling, robotics, stability analysis of neural networks, learning and approximation, data mining and feature extraction, chaos and synchronization, neural fuzzy systems, training and learning algorithms for neural networks, neural network structures, neural networks for pattern recognition, SOMs, ICA/PCA, biomedical applications, feedforward neural networks, recurrent neural networks, neural networks for optimization, support vector machines, fault diagnosis/detection, communications and signal processing, image/video processing, and applications of neural networks.
Practical Iterative Learning Control With Frequency Domain Design And Sampled Data Implementation
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Author : Danwei Wang
language : en
Publisher: Springer
Release Date : 2014-06-19
Practical Iterative Learning Control With Frequency Domain Design And Sampled Data Implementation written by Danwei Wang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-19 with Technology & Engineering categories.
This book is on the iterative learning control (ILC) with focus on the design and implementation. We approach the ILC design based on the frequency domain analysis and address the ILC implementation based on the sampled data methods. This is the first book of ILC from frequency domain and sampled data methodologies. The frequency domain design methods offer ILC users insights to the convergence performance which is of practical benefits. This book presents a comprehensive framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between learning performance and learning stability. The sampled data implementation ensures effective execution of ILC in practical dynamic systems. The presented sampled data ILC methods also ensure the balance of performance and stability of learning process. Furthermore, the presented theories and methodologies are tested with an ILC controlled robotic system. The experimental results show that the machines can work in much higher accuracy than a feedback control alone can offer. With the proposed ILC algorithms, it is possible that machines can work to their hardware design limits set by sensors and actuators. The target audience for this book includes scientists, engineers and practitioners involved in any systems with repetitive operations.
Real Time Iterative Learning Control
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Author : Jian-Xin Xu
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-12
Real Time Iterative Learning Control written by Jian-Xin Xu 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 2008-12-12 with Technology & Engineering categories.
Real-time Iterative Learning Control demonstrates how the latest advances in iterative learning control (ILC) can be applied to a number of plants widely encountered in practice. The book gives a systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in linear and nonlinear plants pervading mechatronics and batch processes are addressed, in particular: ILC design in the continuous- and discrete-time domains; design in the frequency and time domains; design with problem-specific performance objectives including robustness and optimality; design in a modular approach by integration with other control techniques; and design by means of classical tools based on Bode plots and state space.
Linear And Nonlinear Iterative Learning Control
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Author : Jian-Xin Xu
language : en
Publisher: Springer
Release Date : 2003-09-04
Linear And Nonlinear Iterative Learning Control written by Jian-Xin Xu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-09-04 with Science categories.
This monograph summarizes the recent achievements made in the field of iterative learning control. The book is self-contained in theoretical analysis and can be used as a reference or textbook for a graduate level course as well as for self-study. It opens a new avenue towards a new paradigm in deterministic learning control theory accompanied by detailed examples.
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.