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: Discrete-Time Adaptive Iterative Learning Control ISBN: 9811904669 ISBN-13(EAN): 9789811904660 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Описание: This book examines iterative learning control (ILC) with a focus on design and implementation. It presents a framework with various methodologies to ensure the learnable bandwidth in the ILC system to be set with a balance between performance and stability.
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.
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.
Описание: 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.
Описание: 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.
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: Meng Tingting, He Wei Название: Iterative Learning Control for Flexible Structures ISBN: 9811527865 ISBN-13(EAN): 9789811527869 Издательство: Springer Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- Boundary Iterative Learning Control.- ILC for the Vibration Suppression in the Transverse Motion and Rotation.- ILC for the Nonlinearities of Differentiable and Non-Differentiable Inputs.- ILC for the Rejection of Time-Varying and Spatiotemporally Varying Disturbances.- Adaptive ILC for an Euler-Bernoulli Beam with Uncertainties.- ILC for Constant and Varying Trajectories Tracking.- ILC for a Flapping Wing Micro Aerial Vehicle.- ILC for a Flexible Two-Link Manipulator with PDE Model.- Conclusions.
Автор: Meng Tingting, He Wei Название: Iterative Learning Control for Flexible Structures ISBN: 9811527830 ISBN-13(EAN): 9789811527838 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction.- Boundary Iterative Learning Control.- ILC for the Vibration Suppression in the Transverse Motion and Rotation.- ILC for the Nonlinearities of Differentiable and Non-Differentiable Inputs.- ILC for the Rejection of Time-Varying and Spatiotemporally Varying Disturbances.- Adaptive ILC for an Euler-Bernoulli Beam with Uncertainties.- ILC for Constant and Varying Trajectories Tracking.- ILC for a Flapping Wing Micro Aerial Vehicle.- ILC for a Flexible Two-Link Manipulator with PDE Model.- Conclusions.
Автор: Kevin L. Moore Название: Iterative Learning Control for Deterministic Systems ISBN: 1447119142 ISBN-13(EAN): 9781447119142 Издательство: Springer Рейтинг: Цена: 13060.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
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