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 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.
Автор: Zeungnam Bien; Jian-Xin Xu Название: Iterative Learning Control ISBN: 1461375754 ISBN-13(EAN): 9781461375753 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Hyo-Sung Ahn; Kevin L. Moore; YangQuan Chen Название: Iterative Learning Control ISBN: 1849966583 ISBN-13(EAN): 9781849966580 Издательство: Springer Рейтинг: Цена: 17096.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Shows the reader how to use robust iterative learning control in the face of model uncertainty Helps to improve the performance of repetitive electromechanical tasks, widespread in industry Provides a rounded and self-contained approach to the subject of iterative learning control not available elsewhere
Автор: David H. Owens Название: Iterative Learning Control ISBN: 144716928X ISBN-13(EAN): 9781447169284 Издательство: Springer Рейтинг: Цена: 14817.00 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.
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.
Автор: David H. Owens Название: Iterative Learning Control ISBN: 1447167708 ISBN-13(EAN): 9781447167709 Издательство: Springer Рейтинг: Цена: 17097.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
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.
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