Practical Iterative Learning Control with Frequency Domain Design and Sampled Data Implementation, Wang Danwei, Ye Yongqiang, Zhang Bin
Автор: Tongwen Chen; Bruce A. Francis Название: Optimal Sampled-Data Control Systems ISBN: 1447130391 ISBN-13(EAN): 9781447130390 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Part I presents two indirect methods of sampled-data controller design: These approaches include approximations to a real problem, which involves an analogue plant, continuous-time performance specifications, and a sampled-data controller.
Автор: Juan I. Yuz; Graham C. Goodwin Название: Sampled-Data Models for Linear and Nonlinear Systems ISBN: 1447155610 ISBN-13(EAN): 9781447155614 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this book, rather than emphasize differences between sampled-data and continuous-time systems, the authors proceed from the premise that, with modern sampling rates as high as they are, it is more appropriate to emphasise connections and similarities.
Автор: Ichikawa Akira, Katayama Hitoshi Название: Linear Time Varying Systems and Sampled-data Systems ISBN: 1852334398 ISBN-13(EAN): 9781852334390 Издательство: Springer Рейтинг: Цена: 25853.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book gives an introduction to H-infinity and H2 control for linear time-varying systems. Chapter 2 is concerned with continuous-time systems while Chapter 3 is devoted to discrete-time systems.The main aim of this book is to develop the H-infinity and H2 theory for jump systems and to apply it to sampled-data systems. The jump system gives a natural state space representation of sampled-data systems, and original signals and parameters are maintained in the new system. Two earlier chapters serve as preliminaries. Chapter 4 introduces jump systems and develops the H-infinity and H2 theory for them. It is then applied to sampled-data systems in Chapter 5.The new features of this book are as follows: The H-infinity control theory is developed for time-varying systems with initial uncertainty. Recent results on the relation of three Riccati equations are included. The H2 theory usually given for time-invariant systems is extended to time-varying systems. The H-infinity and H2 theory for sampled-data systems is established from the jump system point of view. Extension of the theory to infinite dimensional systems and nonlinear systems is discussed. This covers the sampled-data system with first-order hold. In this book 16 examples and 40 figures of computer simulations are included.The reader can find the H-infinity and H2 theory for linear time-varying systems and sampled-data systems developed in a unified manner. Some arguments inherent to time varying systems or the jump system point of view to sampled-data systems may give new insights into the system theory of time-invariant systems and sampled-data systems.
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.
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.
Автор: J?rgen Ackermann Название: Sampled-Data Control Systems ISBN: 3642825567 ISBN-13(EAN): 9783642825569 Издательство: Springer Рейтинг: Цена: 19591.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapter 4 treats controllability and reach- ability of discrete-time systems, controllability regions for con- strained inputs and the choice of the sampling interval primarily under controllability aspects.
Описание: Engineering systems operate through actuators, most of which will exhibit phenomena such as saturation or zones of no operation, commonly known as dead zones. These are examples of piecewise-affine characteristics, and they can have a considerable impact on the stability and performance of engineering systems. This book targets controller design for piecewise affine systems, fulfilling both stability and performance requirements.The authors present a unified computational methodology for the analysis and synthesis of piecewise affine controllers, taking an approach that is capable of handling sliding modes, sampled-data, and networked systems. They introduce algorithms that will be applicable to nonlinear systems approximated by piecewise affine systems, and they feature several examples from areas such as switching electronic circuits, autonomous vehicles, neural networks, and aerospace applications.Piecewise Affine Control: Continuous-Time, Sampled-Data, and Networked Systems is intended for graduate students, advanced senior undergraduate students, and researchers in academia and industry. It is also appropriate for engineers working on applications where switched linear and affine models are important.
Автор: Juan I. Yuz; Graham C. Goodwin Название: Sampled-Data Models for Linear and Nonlinear Systems ISBN: 1447169972 ISBN-13(EAN): 9781447169970 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this book, rather than emphasize differences between sampled-data and continuous-time systems, the authors proceed from the premise that, with modern sampling rates as high as they are, it is more appropriate to emphasise connections and similarities.
Автор: Hugues Garnier; Liuping Wang Название: Identification of Continuous-time Models from Sampled Data ISBN: 1849967407 ISBN-13(EAN): 9781849967402 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is the first book dedicated to direct continuous-time model identification for 15 years. The CONTSID toolbox discussed in the final chapter gives an overview of developments and practical examples in which MATLAB (R) can be used for direct time-domain identification of continuous-time systems.
Автор: David H. Owens Название: Iterative Learning Control ISBN: 144716928X ISBN-13(EAN): 9781447169284 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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 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.
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