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Iterative Learning Control Algorithms and Experimental Benchmarking

Iterative Learning Control Algorithms and Experimental Benchmarking

by Eric RogersBing Chu Christopher Freeman and others
Hardback
Publication Date: 13/03/2023

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Presents key cutting edge research into the use of iterative learning control

The book discusses the main methods of iterative learning control (ILC) and its interactions, as well as comparator performance that is so crucial to the end user. The book provides an integrated coverage of the major approaches to-date in terms of basic systems theoretic properties, design algorithms, and experimentally measured performance as well the links with repetitive control and other related areas.

Key features:



Provides comprehensive coverage of the main approaches to ILC and their relative advantages and disadvantages.
Presents the leading research in the field along with a unique experimental benchmarking system.
Demonstrates how this approach can extend out from engineering to other areas and, in particular, new research into its use in healthcare systems/ rehabilitation robotics.

The book is essential reading for researchers and graduate students in iterative learning control, repetitive control and, more generally, control systems theory and its applications.
ISBN:
9780470745045
9780470745045
Category:
Automatic control engineering
Format:
Hardback
Publication Date:
13-03-2023
Language:
English
Publisher:
John Wiley & Sons Inc
Country of origin:
United States
Pages:
448
Dimensions (mm):
244x168x30mm
Weight:
0.99kg

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