Iterative Learning Control of Nonlinear Non-Minimum Phase Systems and its Application to System and Model Inversion
2002 (English)Report (Other academic)
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
Iterative methods, learning control, nonlinear systems, convergence analysis, non-minimum phase systems
IdentifiersURN: urn:nbn:se:liu:diva-55871ISRN: LiTH-ISY-R-2440OAI: oai:DiVA.org:liu-55871DiVA: diva2:316664