Iterative Learning Control Robustness and Monotonic Convergence for Interval Systems

Iterative Learning Control Robustness and Monotonic Convergence for Interval Systems / by Hyo-Sung Ahn, Kevin L. Moore, YangQuan Chen.

This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Two key problems with the fundamentals of iterative learning control (ILC) design as treated by existing work are: first, many ILC design strategies assume nominal knowledg...

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Bibliographic Details
Main Authors: Ahn, Hyo-Sung (Author), Moore, Kevin L. (Author), Chen, YangQuan (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: London : Springer London : Imprint: Springer, 2007.
Edition:1st ed. 2007.
Series:Communications and Control Engineering,
Springer eBook Collection.
Subjects:
Control engineering.
System theory.
Artificial intelligence.
Robotics.
Mechatronics.
Bioinformatics.
Biomedical engineering.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Iterative Learning Control Overview
  • An Overview of the ILC Literature
  • The Super-vector Approach
  • Robust Interval Iterative Learning Control
  • Robust Interval Iterative Learning Control: Analysis
  • Schur Stability Radius of Interval Iterative Learning Control
  • Iterative Learning Control Design Based on Interval Model Conversion
  • Iteration-domain Robustness
  • Robust Iterative Learning Control: H? Approach
  • Robust Iterative Learning Control: Stochastic Approaches
  • Conclusions.

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