Observer Based Iterative Learning Controller Design for MIMO Systems in Discrete Time

Rangana N. Jayawardhana, Bijoy K. Ghosh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Observer based learning control algorithms, to synthesize a controller that would make a dynamical system track an a priori known sequence of output vectors, for linear time invariant systems in discrete time, is revisited. For multi input multi output systems, we show that the associated pole placement problem leads to an asymptotically stable iterative scheme, a result that is not trivial in the case of a non-square system. We introduce an obvious block structure implementation of the ILC algorithm that requires only the first Markov parameter matrix of the system. The closed loop pole locations, we observe through simulations, dictate the transient response of the system during learning process. Large values of the transient response is undesirable, and we show how to clip off such responses, while maintaining eventual convergence of the iteration.

Original languageEnglish
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6402-6408
Number of pages7
ISBN (Print)9781538654286
DOIs
StatePublished - Aug 9 2018
Event2018 Annual American Control Conference, ACC 2018 - Milwauke, United States
Duration: Jun 27 2018Jun 29 2018

Publication series

NameProceedings of the American Control Conference
Volume2018-June
ISSN (Print)0743-1619

Conference

Conference2018 Annual American Control Conference, ACC 2018
CountryUnited States
CityMilwauke
Period06/27/1806/29/18

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    Jayawardhana, R. N., & Ghosh, B. K. (2018). Observer Based Iterative Learning Controller Design for MIMO Systems in Discrete Time. In 2018 Annual American Control Conference, ACC 2018 (pp. 6402-6408). [8431853] (Proceedings of the American Control Conference; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2018.8431853