Real-time Iterative Learning Control: Design and Applications

by Jian-Xin Xu, Sanjib K. Panda, Tong Heng Lee

Overview

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.

Product Details

ISBN-13:	9781849968249
Publisher:	Springer London
Publication date:	12/10/2010
Series:	Advances in Industrial Control , #5
Edition description:	Softcover reprint of hardcover 1st ed. 2009
Pages:	194
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

to ILC: Concepts, Schematics, and Implementation.- Robust Optimal ILC Design for Precision Servo: Application to an XY Table.- ILC for Precision Servo with Input Non-linearities: Application to a Piezo Actuator.- ILC for Process Temperature Control: Application to a Water-heating Plant.- ILC with Robust Smith Compensator: Application to a Furnace Reactor.- Plug-in ILC Design for Electrical Drives: Application to a PM Synchronous Motor.- ILC for Electrical Drives: Application to a Switched Reluctance Motor.- Optimal Tuning of PID Controllers Using Iterative Learning Approach.- Calibration of Micro-robot Inverse Kinematics Using Iterative Learning Approach.- Conclusion.