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Realtime Iterative Learning Control Design And Applications 1st Edition Jianxin Xu

  • SKU: BELL-2120824
Realtime Iterative Learning Control Design And Applications 1st Edition Jianxin Xu
$ 31.00 $ 45.00 (-31%)

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Realtime Iterative Learning Control Design And Applications 1st Edition Jianxin Xu instant download after payment.

Publisher: Springer-Verlag London
File Extension: PDF
File size: 5.42 MB
Pages: 194
Author: Jian-Xin Xu, Sanjib K. Panda, Tong Heng Lee (auth.)
ISBN: 9781848821743, 9781848821750, 1848821743, 1848821751
Language: English
Year: 2009
Edition: 1

Product desciption

Realtime Iterative Learning Control Design And Applications 1st Edition Jianxin Xu by Jian-xin Xu, Sanjib K. Panda, Tong Heng Lee (auth.) 9781848821743, 9781848821750, 1848821743, 1848821751 instant download after payment.

Iterative learning control (ILC) has been a major control design methodology for twenty years; numerous algorithms have been developed to solve real-time control problems, from MEMS to batch reactors, characterised by repetitive control operations.

Real-time Iterative Learning Control demonstrates how the latest advances in ILC can be applied to a number of plants widely encountered in practice. The authors provide a hitherto lacking systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in the linear and nonlinear plants that pervade mechatronics and batch processes are addressed. In particular, the book discusses:

• ILC design in the continuous- and discrete-time domains;

• design in the frequency and time domains;

• design with problem-specific performance objectives including robustness and optimality;

• design by means of classical tools based on Bode plots and state space; and

• iterative-learning-based parametric identification.

Real-time Iterative Learning Control will interest control engineers looking for examples of how this important control technique can be applied to a variety of real-life problems. With its systematic formulation and analysis of different system properties and performance and its exposition of open problems, academics and graduate students working in control will find it a useful reference to the current status of ILC.

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