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Estimation Based Multiple Model Iterative Learning Control

Freeman, C.T. and French, M. (2015) Estimation Based Multiple Model Iterative Learning Control At 54th IEEE Conference on Decision and Control. , pp. 6075-6080.

Record type: Conference or Workshop Item (Other)


An iterative learning control (ILC) framework is developed which provides robust stability and performance bounds under the assumption that the true plant model belongs to a plant uncertainty set that is specified by the designer. A set of candidate plant models is defined comprising hypotheses of the ‘true’ plant model, and after each ILC trial the update used is chosen to correspond to the current best plant hypothesis from the observed history via an optimisation based estimation process. A comprehensive design procedure for the switched multiple model ILC system is presented which is applicable to a general class of ILC update.

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Published date: 1 December 2015
Venue - Dates: 54th IEEE Conference on Decision and Control, 2015-12-01
Organisations: EEE


Local EPrints ID: 379655
PURE UUID: a6f6ed54-fcac-4d71-83f9-e1e4c45abc93

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Date deposited: 25 Jul 2015 19:36
Last modified: 17 Jul 2017 20:41

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