Overview
- Provides comprehensive coverage of this new and important area of modern control engineering
- Several practical applications are demonstrated
- Both theoretical and practical aspects of ILC are considered
Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 248)
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About this book
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
Table of contents (12 chapters)
Bibliographic Information
Book Title: Iterative Learning Control
Book Subtitle: Convergence, Robustness and Applications
Editors: Yangquan Chen, Changyun Wen
Series Title: Lecture Notes in Control and Information Sciences
DOI: https://doi.org/10.1007/BFb0110114
Publisher: Springer London
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag London 1999
Softcover ISBN: 978-1-85233-190-0Published: 22 September 1999
eBook ISBN: 978-1-84628-539-4Published: 03 October 2007
Series ISSN: 0170-8643
Series E-ISSN: 1610-7411
Edition Number: 1
Number of Pages: XII, 204
Number of Illustrations: 2 b/w illustrations
Topics: Control, Robotics, Mechatronics, Computational Intelligence