Real-time Iterative Learning Control

Jian-Xin Xu|Sanjib K. Panda|Tong Heng Lee

ISBN 10: 1849968241 / ISBN 13: 9781849968249

Published by Springer London, 2010

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides the industry-based control engineer with a practical reference for designing and implementing iterative learning control systems in their own plants based on many practical examplesGives the academic researcher systematic formulation and .

Seller Inventory # 4288897

Bibliographic Details

• Title: Real-time Iterative Learning Control
• Publisher: Springer London
• Publication Date: 2010
• Language: English
• ISBN 10: 1849968241
• ISBN 13: 9781849968249
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Real-time Iterative Learning Control demonstrates how the latest advances in iterative learning control (ILC) can be applied to a number of plants widely encountered in practice. The book gives a systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in linear and nonlinear plants pervading mechatronics and batch processes are addressed, in particular: ILC design in the continuous- and discrete-time domains; design in the frequency and time domains; design with problem-specific performance objectives including robustness and optimality; design in a modular approach by integration with other control techniques; and design by means of classical tools based on Bode plots and state space.

From the Back Cover

Iterative learning control (ILC) has been a major control design methodology for twenty years; numerous algorithms have been developed to solve real-time control problems, from MEMS to batch reactors, characterised by repetitive control operations.

Real-time Iterative Learning Control demonstrates how the latest advances in ILC can be applied to a number of plants widely encountered in practice. The authors provide a hitherto lacking systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in the linear and nonlinear plants that pervade mechatronics and batch processes are addressed. In particular, the book discusses:

• ILC design in the continuous- and discrete-time domains;

• design in the frequency and time domains;

• design with problem-specific performance objectives including robustness and optimality;

• design by means of classical tools based on Bode plots and state space; and

• iterative-learning-based parametric identification.

Real-time Iterative Learning Control will interest control engineers looking for examples of how this important control technique can be applied to a variety of real-life problems. With its systematic formulation and analysis of different system properties and performance and its exposition of open problems, academics and graduate students working in control will find it a useful reference to the current status of ILC.