Iterative Learning Control For Nonlinear Time Delay System
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Iterative Learning Control For Nonlinear Time Delay System
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Author : Jianming Wei
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Iterative Learning Control For Nonlinear Time Delay System written by Jianming Wei and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Technology & Engineering categories.
This book focuses on adaptive iterative learning control problem for nonlinear time-delay systems.A universal adaptive learning control scheme is provided for a wide classes of nonlinear systems with time-varying delay and input nonlinearity. Proceeding from easy to difficult, this book deals with the adaptive iterative learning control problems for parameterized nonlinear time-delay systems, non-parameterized nonlinear time-delay systems, nonlinear time-delay systems with unknown control direction and nonlinear time-delay systems with un-measurable states. The proposed control schemes can be extended to the adaptive learning control problem for wider classes of nonlinear systems revelent to abovementioned nonlinear systems.The topics presented in this book are research hot spots of iterative learning control. This book will be a valuable reference for researchers and students working or studying in this area.
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.
Iterative Learning Control For Flexible Structures
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Author : Tingting Meng
language : en
Publisher: Springer Nature
Release Date : 2020-03-23
Iterative Learning Control For Flexible Structures written by Tingting Meng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-23 with Technology & Engineering categories.
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.
Optimal Fractional Order Predictive Pi Controllers
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Author : Arun Mozhi Devan Panneer Selvam
language : en
Publisher: Springer Nature
Release Date : 2022-11-01
Optimal Fractional Order Predictive Pi Controllers written by Arun Mozhi Devan Panneer Selvam and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-01 with Technology & Engineering categories.
This book presents the study to design, develop, and implement improved PI control techniques using dead-time compensation, structure enhancements, learning functions and fractional ordering parameters. Two fractional-order PI controllers are proposed and designed: fractional-order predictive PI and hybrid iterative learning based fractional-order predictive PI controller. Furthermore, the proposed fractional-order control strategies and filters are simulated over first- and second-order benchmark process models and further validated using the real-time experimentation of the pilot pressure process plant. In this book, five chapters are structured with a proper sequential flow of details to provide a better understanding for the readers. A general introduction to the controllers, filters and optimization techniques is presented in Chapter 1. Reviews of the PI controllers family and their modifications are shown in the initial part of Chapter 2, followed by the development of the proposed fractional-order predictive PI (FOPPI) controller with dead-time compensation ability. In the first part of chapter 3, a review of the PI based iterative learning controllers, modified structures of the ILC and their modifications are presented. Then, the design of the proposed hybrid iterative learning controller-based fractional-order predictive PI controller based on the current cyclic feedback structure is presented. Lastly, the results and discussion of the proposed controller on benchmark process models and the real-time experimentation of the pilot pressure process plant are given. Chapter 4 presents the development of the proposed filtering techniques and their performance comparison with the conventional methods. Chapter 5 proposes the improvement of the existing sine cosine algorithm (SCA) and arithmetic optimization algorithm (AOA) to form a novel arithmetic-trigonometric optimization algorithm (ATOA) to accelerate the rate of convergence in lesser iterations with mitigation towards getting caught in the same local position. The performance analysis of the optimization algorithm will be carried out on benchmark test functions and the real-time pressure process plant.
Adaptive Control For Robotic Manipulators
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Author : Dan Zhang
language : en
Publisher: CRC Press
Release Date : 2017-02-03
Adaptive Control For Robotic Manipulators written by Dan Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-03 with Science categories.
The robotic mechanism and its controller make a complete system. As the robotic mechanism is reconfigured, the control system has to be adapted accordingly. The need for the reconfiguration usually arises from the changing functional requirements. This book will focus on the adaptive control of robotic manipulators to address the changed conditions. The aim of the book is to summarise and introduce the state-of-the-art technologies in the field of adaptive control of robotic manipulators in order to improve the methodologies on the adaptive control of robotic manipulators. Advances made in the past decades are described in the book, including adaptive control theories and design, and application of adaptive control to robotic manipulators.
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.
Linear And Nonlinear Iterative Learning Control
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Author : Jian-Xin Xu
language : en
Publisher: Springer
Release Date : 2003-06-23
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 2003-06-23 with Technology & Engineering 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 Equations With Fractional Derivatives And Impulses
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Author : JinRong Wang
language : en
Publisher: Springer Nature
Release Date : 2021-12-10
Iterative Learning Control For Equations With Fractional Derivatives And Impulses written by JinRong Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-10 with Mathematics categories.
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.
Iterative Learning Stabilization And Fault Tolerant Control For Batch Processes
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Author : Limin Wang
language : en
Publisher: Springer
Release Date : 2019-03-18
Iterative Learning Stabilization And Fault Tolerant Control For Batch Processes written by Limin Wang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-18 with Technology & Engineering categories.
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.
Predictive Learning Control For Unknown Nonaffine Nonlinear Systems
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Author : Qiongxia Yu
language : en
Publisher: Springer Nature
Release Date : 2023-02-17
Predictive Learning Control For Unknown Nonaffine Nonlinear Systems written by Qiongxia Yu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-17 with Technology & Engineering categories.
This book investigates both theory and various applications of predictive learning control (PLC) which is an advanced technology for complex nonlinear systems. To avoid the difficult modeling problem for complex nonlinear systems, this book begins with the design and theoretical analysis of PLC method without using mechanism model information of the system, and then a series of PLC methods is designed that can cope with system constraints, varying trial lengths, unknown time delay, and available and unavailable system states sequentially. Applications of the PLC on both railway and urban road transportation systems are also studied. The book is intended for researchers, engineers, and graduate students who are interested in predictive control, learning control, intelligent transportation systems and related fields.