Overview

This overview of iterative learning control theory and techniques is relevant to industrial automation, and focuses on research directions for the 21st century. It examines the important aspects of this emerging technology, and provides coverage of ILC's history, its expanding real-world applications, and its robustness and convergence. Also included are sampled-data and discrete-time issues, design guidelines and quadratic criterion, the ability of dynamic systems to learn, time-delay problems, integration (with neural network, fuzzy logic and wavelet), direct learning, and identification, in addition to ILC's possible applications to batch and welding processes, neuromuscular stimulation, and other fast-changing fields. This volume should be of interest to researchers and engineers in robotics, automation, systems and control, and signal processing.

Full Product Details

Author:   Zeungnam Bien ,  Jian-Xin Xu
Publisher:   Springer
Imprint:   Springer
Edition:   1998 ed.
Dimensions:   Width: 15.50cm , Height: 2.30cm , Length: 23.50cm
Weight:   1.640kg
ISBN:  

9780792382133

ISBN 10:   0792382137
Pages:   373
Publication Date:   31 July 1998
Audience:   Professional and scholarly ,  General/trade ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD  
We will order this item for you from a manufatured on demand supplier.

Table of Contents

I General Introduction to Iterative Learning Control.- A Brief History of Iterative Learning Control.- The Frontiers of Iterative Learning Control.- II Property Analysis of Iterative Learning Control.- Robustness and Convergence of A PD-type Iterative Learning Controller.- Ability of Learning Comes from Passivity and Dissipativity of System Dynamics.- On the Iterative Learning Control of Sampled-Data Systems.- High-order Iterative Learning Control of Discrete-time Nonlinear Systems Using Current Iteration Tracking Error.- III The Design Issues of Iterative Learning Control.- Designing Iterative Learning and Repetitive Controllers.- Design of an ILC for Linear Systems with Time-Delay and Initial State Error.- Design of Quadratic Criterion-based Iterative Learning Control.- Robust ILC with Current Feedback for Uncertain Linear Systems.- IV Integration of Iterative Learning Control with other Intelligent Controls.- Model Reference Learning Control with a Wavelet Network.- Neural-based Iterative Learning Control.- Adaptive Learning Control of Robotic Systems and Its Extension to a Class of Nonlinear Systems.- Direct Learning Control of Non-uniform Trajectories.- System Identification and Learning Control.- V Implementations of Iterative Learning Control Method.- Model-Based Predictive Control Combined with Iterative Learning for Batch or Repetitive Processe.- Iterative Learning Control with Non-Standard Assumptions Applied to the Control of Gas-Metal Arc Welding.- Robust Control of Functional Neuromuscular Stimulation System by Discrete-time Iterative Learning.- About the Editors.

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