Low-order system identification and optimal control of intersample behavior in ILC

Authors:
Tom Oomen;Jeroen Van De Wijdeven;Okko Bosgra
Affiliations:
Eindhoven University of Technology, Eindhoven, The Netherlands;Eindhoven University of Technology, Eindhoven, The Netherlands;Eindhoven University of Technology, Eindhoven, The Netherlands
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

Citing 5
Cited 0

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Brief paper: Suppressing intersample behavior in iterative learning control

Automatica (Journal of IFAC)
Brief On the design of ILC algorithms using optimization

Automatica (Journal of IFAC)

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Abstract

Iterative Learning Control (ILC) enables high tracking performance of batch repetitive processes. Common ILC approaches resort to discrete time system representations and hence are not able to guarantee good intersample behavior in case the underlying system evolves in continuous time. The aim of this paper is to explicitly deal with the intersample behavior in ILC. A multirate, parametric, and low-order approach to both identification for ILC and subsequent optimal ILC is presented that results in a low computational burden. The approach appropriately deals with the time-varying nature of multirate systems. The proposed multirate identification and ILC algorithms are shown to outperform common ILC approaches in a simulation example.