Advertisement

Discrete-Time Iterative Learning Control

  • Khalid AbidiEmail author
  • Jian-Xin Xu
Chapter
  • 1.4k Downloads
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 23)

Abstract

In this study the convergence properties of iterative learning control (ILC) algorithms are discussed. The analysis is carried out in a framework using linear iterative systems, which enables several results from the theory of linear systems to be applied. This makes it possible to analyse both first-order and high-order ILC algorithms in both the time and frequency domains. The time and frequency domain results can also be tied together in a clear way. Illustrative examples are presented to support the analytical results.

Keywords

Tracking Error Iterative Learning Control Learning Gain Learning Function Nyquist Diagram 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media Singapore 2015

Authors and Affiliations

  1. 1.Newcastle UniversityAng Mo KioSingapore
  2. 2.Department of Electrical and Computer EngineeringNational University of SingaporeKent Ridge CrescentSingapore

Personalised recommendations