Iterative Learning Control Algorithms and Experimental Benchmarking

Eric Rogers, Christopher Freeman, Paul Lewin, Bing Chu

ISBN 10: 0470745045 / ISBN 13: 9780470745045

Published by John Wiley and Sons Inc, US, 2023

About this Item

Iterative Learning CONTROL ALGORITHMS AND EXPERIMENTAL BENCHMARKING Iterative Learning Control Algorithms and Experimental Benchmarking 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 integrated coverage of the major approaches to-date in terms of basic systems, theoretic properties, design algorithms, and experimentally measured performance, as well as 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 experimental benchmarking results. 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.

Seller Inventory # LU-9780470745045

Bibliographic Details

• Title: Iterative Learning Control Algorithms and Experimental Benchmarking
• Publisher: John Wiley and Sons Inc, US
• Publication Date: 2023
• Language: English
• ISBN 10: 0470745045
• ISBN 13: 9780470745045
• Binding: Hardback
• Condition: New

About this title

Synopsis

Iterative Learning CONTROL ALGORITHMS AND EXPERIMENTAL BENCHMARKING

Iterative Learning Control Algorithms and Experimental Benchmarking

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 integrated coverage of the major approaches to-date in terms of basic systems, theoretic properties, design algorithms, and experimentally measured performance, as well as 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 experimental benchmarking results.
• 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.

About the Author

Professor Eric Rogers, Dr. Bing Chu, Professor Christopher Freeman, and Professor Paul Lewin, University of Southampton, UK