About this book

Introduction

This book provides readers with a comprehensive coverage of iterative learning control. The book can be used as a text or reference for a course at graduate level and is also suitable for self-study and for industry-oriented courses of continuing education.
Ranging from aerodynamic curve identification robotics to functional neuromuscular stimulation, Iterative Learning Control (ILC), started in the early 80s, is found to have wide applications in practice. Generally, a system under control may have uncertainties in its dynamic model and its environment. One attractive point in ILC lies in the utilisation of the system repetitiveness to reduce such uncertainties and in turn to improve the control performance by operating the system repeatedly. This monograph emphasises both theoretical and practical aspects of ILC. It provides some recent developments in ILC convergence and robustness analysis. The book also considers issues in ILC design. Several practical applications are presented to illustrate the effectiveness of ILC. The applied examples provided in this monograph are particularly beneficial to readers who wish to capitalise the system repetitiveness to improve system control performance.

Keywords

Tracking control feedback filtering learning modeling nonlinear system robot robotics

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0110114
  • Copyright Information Springer-Verlag London Limited 1999
  • Publisher Name Springer, London
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-85233-190-0
  • Online ISBN 978-1-84628-539-4
  • Series Print ISSN 0170-8643
  • Series Online ISSN 1610-7411
  • About this book