Analysis of Linear Iterative Learning Control Schemes -A 2D Systems/Repetitive Processes Approach

  • Authors:

  • D. H. Owens;N. Amann;E. Rogers;M. French

  • Affiliations:

  • Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK;Daimlerchrysler, Berlin, Germany;Department of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK;Department of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK

  • Venue:
  • Multidimensional Systems and Signal Processing - Recent progress in multidimensional control theory and applications
  • Year:
  • 2000

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Abstract

This paperfirst develops results on the stability and convergence propertiesof a general class of iterative learning control schemes using,in the main, theory first developed for the branch of 2D linearsystems known as linear repetitive processes. A general learninglaw that uses information from the current and a finite numberof previous trials is considered and the results, in the formof fundamental limitations on the benefits of using this law,are interpreted in terms of basic systems theoretic conceptssuch as the relative degree and minimum phase characteristicsof the example under consideration. Following this, previouslyreported powerful 2D predictive and adaptive control algorithmsare reviewed. Finally, new iterative adaptive learning controllaws which solve iterative learning control algorithms underweak assumptions are developed.