Discrete-Time Adaptive Iterative Learning Control, Chi

Автор: Wei
Название: Iterative Learning Control for Nonlinear Time-Delay System
ISBN: 9811963169 ISBN-13(EAN): 9789811963162
Издательство: Springer
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Цена: 139750.00 T
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Описание: 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.

Автор: Zeungnam Bien; Jian-Xin Xu
Название: Iterative Learning Control
ISBN: 1461375754 ISBN-13(EAN): 9781461375753
Издательство: Springer
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Цена: 139750.00 T
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Описание: 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.

Автор: Dong Shen
Название: Iterative Learning Control with Passive Incomplete Information
ISBN: 9811082669 ISBN-13(EAN): 9789811082665
Издательство: Springer
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Цена: 130430.00 T
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Описание: 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.

Автор: Chi Ronghu, Lin Na, Zhang Huimin
Название: Discrete-Time Adaptive Iterative Learning Control: From Model-Based to Data-Driven
ISBN: 9811904634 ISBN-13(EAN): 9789811904639
Издательство: Springer
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Цена: 121110.00 T
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Описание: 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.

Автор: Chi
Название: Data-Driven Iterative Learning Control for Discrete-Time Systems
ISBN: 9811959498 ISBN-13(EAN): 9789811959493
Издательство: Springer
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Цена: 139750.00 T
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Описание: 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.

Автор: Pedro Albertos; Antonio Sala Piqueras
Название: Iterative Identification and Control
ISBN: 1447110986 ISBN-13(EAN): 9781447110989
Издательство: Springer
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Цена: 139750.00 T
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Описание: An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.

Автор: Wang
Название: Iterative Learning Control for Equations with Fractional Derivatives and Impulses
ISBN: 9811682461 ISBN-13(EAN): 9789811682469
Издательство: Springer
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Цена: 111790.00 T
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Описание: 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.

Автор: Rogers, E
Название: Iterative learning control algorithms and experimental benchmarking
ISBN: 0470745045 ISBN-13(EAN): 9780470745045
Издательство: Wiley
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Цена: 89760.00 T
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Описание: 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.

Автор: Wang Jinrong, Liu Shengda, Fečkan Michal
Название: Iterative Learning Control for Equations with Fractional Derivatives and Impulses
ISBN: 9811682437 ISBN-13(EAN): 9789811682438
Издательство: Springer
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Цена: 111790.00 T
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Описание: 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.

Автор: Kevin L. Moore
Название: Iterative Learning Control for Deterministic Systems
ISBN: 1447119142 ISBN-13(EAN): 9781447119142
Издательство: Springer
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Цена: 87070.00 T
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Описание: 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.

Автор: Chris T. Freeman; Eric Rogers; Jane H. Burridge; A
Название: Iterative Learning Control for Electrical Stimulation and Stroke Rehabilitation
ISBN: 1447167252 ISBN-13(EAN): 9781447167259
Издательство: Springer
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Цена: 51230.00 T
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Описание: Iterative learning control (ILC) has its origins in the control of processes that perform a task repetitively with a view to improving accuracy from trial to trial by using information from previous executions of the task. This brief shows how a classic application of this technique – trajectory following in robots – can be extended to neurological rehabilitation after stroke. Regaining upper limb movement is an important step in a return to independence after stroke, but the prognosis for such recovery has remained poor. Rehabilitation robotics provides the opportunity for repetitive task-oriented movement practice reflecting the importance of such intense practice demonstrated by conventional therapeutic research and motor learning theory. Until now this technique has not allowed feedback from one practice repetition to influence the next, also implicated as an important factor in therapy. The authors demonstrate how ILC can be used to adjust external functional electrical stimulation of patients’ muscles while they are repeatedly performing a task in response to the known effects of stimulation in previous repetitions. As the motor nerves and muscles of the arm reaquire the ability to convert an intention to move into a motion of accurate trajectory, force and rapidity, initially intense external stimulation can now be scaled back progressively until the fullest possible independence of movement is achieved.

Автор: David H. Owens
Название: Iterative Learning Control
ISBN: 144716928X ISBN-13(EAN): 9781447169284
Издательство: Springer
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Цена: 113180.00 T
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Описание: Iterative Learning Control: Background and Review. Mathematical and Linear Modelling Methodologies.- Norm Optimal Iterative Learning Control: An Optimal Control Perspective.- Predicting the Effects of Non-minimum-phase Zeros.- Predictive Norm Optimal Iterative Learning Control.- Other Applications of Norm Optimal Iterative Learning Control.- Successive Projection Algorithms.- Parameter Optimal Iterative Learning Control.- Robustness of Parameter Optimal Iterative Learning Control.- Multi-parameter Optimal Iterative Learning Control.- No Normal 0 false false false EN-GB X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name: "Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow: yes; mso-style-priority:99; mso-style-parent: ""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination: widow-orphan; font-size:11.0pt; font-family: "Calibri","sans-serif"; mso-ascii-font-family: Calibri; mso-ascii-theme-font: minor-latin; mso-hansi-font-family: Calibri; mso-hansi-theme-font: minor-latin; mso-fareast-language: EN-US;} nlinear Iterative Learning Control and Optimization.