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Iterative Learning Control of Nonlinear Non-Minimum Phase Systems and its Application to System and Model Inversion
Royal Institute of Technology, Sweden.
Royal Institute of Technology, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2002 (English)Report (Other academic)
Abstract [en]

In this contribution we place ILC in the realm of numerical optimization. This clarifies the role played by the design variables and how they affect e.g. convergence properties. We give a model based interpretation of these design variables and also a sufficient condition for convergence of ILC which is similar in spirit to the sufficient and necessary condition previously derived for linear systems. This condition shows that the desired performance has to be traded against modelling accuracy. Finally, one of the main benefits of ILC when non-minimum phase systems are concerned, the possibility of non-causal control, is given a comprehensive coverage.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2002. , 4 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2440
Keyword [en]
Iterative methods, learning control, nonlinear systems, convergence analysis, non-minimum phase systems
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-55871ISRN: LiTH-ISY-R-2440OAI: diva2:316664
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-02Bibliographically approved

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Markusson, Ola
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Automatic ControlThe Institute of Technology
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ReferencesLink to record
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