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Iterative Learning Control Algorithms and Experimental Benchmarking

  • ID: 2171158
  • Book
  • April 2020
  • 400 Pages
  • John Wiley and Sons Ltd

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.

Note: Product cover images may vary from those shown
Eric Rogers
Bing Chu
Christopher Freeman
Paul Lewin
David H. Owens
Note: Product cover images may vary from those shown