Real Time Iterative Learning Control

Author : Jian-Xin Xu,Sanjib K. Panda,Tong Heng Lee
Publisher : Springer Science & Business Media
Page : 204 pages
File Size : 52,7 Mb
Release : 2008-12-12
Category : Technology & Engineering
ISBN : 9781848821750

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Real-time Iterative Learning Control by Jian-Xin Xu,Sanjib K. Panda,Tong Heng Lee Pdf

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.

Author : Jian-Xin Xu,Sanjib K. Panda,Tong Heng Lee
Publisher : Unknown
Page : 212 pages
File Size : 48,8 Mb
Release : 2009-02-23
Category : Electronic
ISBN : 184882176X

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Real-Time Iterative Learning Control by Jian-Xin Xu,Sanjib K. Panda,Tong Heng Lee Pdf

Author : Ronghu Chi,Yu Hui,Zhongsheng Hou
Publisher : Springer Nature
Page : 239 pages
File Size : 42,5 Mb
Release : 2022-11-15
Category : Technology & Engineering
ISBN : 9789811959509

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Data-Driven Iterative Learning Control for Discrete-Time Systems by Ronghu Chi,Yu Hui,Zhongsheng Hou Pdf

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.

Author : Zeungnam Bien,Jian-Xin Xu
Publisher : Springer Science & Business Media
Page : 384 pages
File Size : 46,8 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461556299

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Iterative Learning Control by Zeungnam Bien,Jian-Xin Xu Pdf

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.

Author : Eric Rogers,Bing Chu,Christopher Freeman,Paul Lewin
Publisher : John Wiley & Sons
Page : 454 pages
File Size : 55,7 Mb
Release : 2023-01-12
Category : Technology & Engineering
ISBN : 9781118535370

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Iterative Learning Control Algorithms and Experimental Benchmarking by Eric Rogers,Bing Chu,Christopher Freeman,Paul Lewin Pdf

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.

Author : Kevin L. Moore
Publisher : Springer Science & Business Media
Page : 158 pages
File Size : 48,5 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781447119128

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Iterative Learning Control for Deterministic Systems by Kevin L. Moore Pdf

The material presented in this book addresses the analysis and design of learning control systems. It begins with an introduction to the concept of learning control, including a comprehensive literature review. The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem. Additionally, several design methods are given for LTI learning control, incorporating a technique based on parameter estimation and a one-step learning control algorithm for finite-horizon problems. Further chapters focus upon learning control for deterministic nonlinear systems, and a time-varying learning controller is presented which can be applied to a class of nonlinear systems, including the models of typical robotic manipulators. The book concludes with the application of artificial neural networks to the learning control problem. Three specific ways to neural nets for this purpose are discussed, including two methods which use backpropagation training and reinforcement learning. The appendices in the book are particularly useful because they serve as a tutorial on artificial neural networks.

Author : Shiping Yang,Jian-Xin Xu,Xuefang Li,Dong Shen
Publisher : John Wiley & Sons
Page : 272 pages
File Size : 47,7 Mb
Release : 2017-03-03
Category : Technology & Engineering
ISBN : 9781119189060

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Iterative Learning Control for Multi-agent Systems Coordination by Shiping Yang,Jian-Xin Xu,Xuefang Li,Dong Shen Pdf

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

Author : Hyo-Sung Ahn,Kevin L. Moore,YangQuan Chen
Publisher : Springer Science & Business Media
Page : 237 pages
File Size : 47,8 Mb
Release : 2007-06-28
Category : Technology & Engineering
ISBN : 9781846288593

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Iterative Learning Control by Hyo-Sung Ahn,Kevin L. Moore,YangQuan Chen Pdf

This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.

Author : David H. Owens
Publisher : Springer
Page : 456 pages
File Size : 42,5 Mb
Release : 2015-10-31
Category : Technology & Engineering
ISBN : 9781447167723

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Iterative Learning Control by David H. Owens Pdf

This book develops a coherent and quite general theoretical approach to algorithm design for iterative learning control based on the use of operator representations and quadratic optimization concepts including the related ideas of inverse model control and gradient-based design. Using detailed examples taken from linear, discrete and continuous-time systems, the author gives the reader access to theories based on either signal or parameter optimization. Although the two approaches are shown to be related in a formal mathematical sense, the text presents them separately as their relevant algorithm design issues are distinct and give rise to different performance capabilities. Together with algorithm design, the text demonstrates the underlying robustness of the paradigm and also includes new control laws that are capable of incorporating input and output constraints, enable the algorithm to reconfigure systematically in order to meet the requirements of different reference and auxiliary signals and also to support new properties such as spectral annihilation. Iterative Learning Control will interest academics and graduate students working in control who will find it a useful reference to the current status of a powerful and increasingly popular method of control. The depth of background theory and links to practical systems will be of use to engineers responsible for precision repetitive processes.

Author : Tingting Meng,Wei He
Publisher : Springer Nature
Page : 190 pages
File Size : 49,8 Mb
Release : 2020-03-23
Category : Technology & Engineering
ISBN : 9789811527845

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Iterative Learning Control for Flexible Structures by Tingting Meng,Wei He Pdf

This book presents iterative learning control (ILC) to address practical issues of flexible structures. It is divided into four parts: Part I provides a general introduction to ILC and flexible structures, while Part II proposes various types of ILC for simple flexible structures to address issues such as vibration, input saturation, input dead-zone, input backlash, external disturbances, and trajectory tracking. It also includes simple partial differential equations to deal with the common problems of flexible structures. Part III discusses the design of ILC for flexible micro aerial vehicles and two-link manipulators, and lastly, Part IV offers a summary of the topics covered. Unlike most of the literature on ILC, which focuses on ordinary differential equation systems, this book explores distributed parameter systems, which are comparatively less stabilized through ILC.Including a comprehensive introduction to ILC of flexible structures, it also examines novel approaches used in ILC to address input constraints and disturbance rejection. This book is intended for researchers, graduate students and engineers in various fields, such as flexible structures, external disturbances, nonlinear inputs and tracking control.

Author : Limin Wang,Ridong Zhang,Furong Gao
Publisher : Springer
Page : 323 pages
File Size : 46,5 Mb
Release : 2019-03-18
Category : Technology & Engineering
ISBN : 9789811357909

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Iterative Learning Stabilization and Fault-Tolerant Control for Batch Processes by Limin Wang,Ridong Zhang,Furong Gao Pdf

This book is based on the authors’ research on the stabilization and fault-tolerant control of batch processes, which are flourishing topics in the field of control system engineering. It introduces iterative learning control for linear/nonlinear single/multi-phase batch processes; iterative learning optimal guaranteed cost control; delay-dependent iterative learning control; and iterative learning fault-tolerant control for linear/nonlinear single/multi-phase batch processes. Providing important insights and useful methods and practical algorithms that can potentially be applied in batch process control and optimization, it is a valuable resource for researchers, scientists, and engineers in the field of process system engineering and control engineering.

Author : Ronghu Chi,Na Lin,Huimin Zhang,Ruikun Zhang
Publisher : Springer Nature
Page : 211 pages
File Size : 41,6 Mb
Release : 2022-03-21
Category : Technology & Engineering
ISBN : 9789811904646

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Discrete-Time Adaptive Iterative Learning Control by Ronghu Chi,Na Lin,Huimin Zhang,Ruikun Zhang Pdf

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.

Author : JinRong Wang,Shengda Liu,Michal Fečkan
Publisher : Springer Nature
Page : 263 pages
File Size : 42,6 Mb
Release : 2021-12-10
Category : Mathematics
ISBN : 9789811682445

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Iterative Learning Control for Equations with Fractional Derivatives and Impulses by JinRong Wang,Shengda Liu,Michal Fečkan Pdf

This book introduces iterative learning control (ILC) and its applications to the new equations such as fractional order equations, impulsive equations, delay equations, and multi-agent systems, which have not been presented in other books on conventional fields. ILC is an important branch of intelligent control, which is applicable to robotics, process control, and biological systems. The fractional version of ILC updating laws and formation control are presented in this book. ILC design for impulsive equations and inclusions are also established. The broad variety of achieved results with rigorous proofs and many numerical examples make this book unique. This book is useful for graduate students studying ILC involving fractional derivatives and impulsive conditions as well as for researchers working in pure and applied mathematics, physics, mechanics, engineering, biology, and related disciplines.

Author : Jian-Xin Xu,Ying Tan
Publisher : Springer
Page : 175 pages
File Size : 41,7 Mb
Release : 2003-09-04
Category : Science
ISBN : 9783540448457

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Linear and Nonlinear Iterative Learning Control by Jian-Xin Xu,Ying Tan Pdf

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.

Author : Dong Shen,Xuefang Li
Publisher : Springer
Page : 256 pages
File Size : 52,9 Mb
Release : 2019-01-29
Category : Technology & Engineering
ISBN : 9789811361364

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Iterative Learning Control for Systems with Iteration-Varying Trial Lengths by Dong Shen,Xuefang Li Pdf

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.