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Experimental implementation of an iteration-varying optimal stochastic iterative learning control algorithm

Experimental implementation of an iteration-varying optimal stochastic iterative learning control algorithm
Experimental implementation of an iteration-varying optimal stochastic iterative learning control algorithm
A number of iterative learning control algorithms have been developed in a stochastic setting in recent years. The results currently available are in the form of fundamental systems theoretical properties and associated algorithm development. This paper reports results from the application of a stochastic algorithm on a gantry robot system that has been used in the benchmarking a range of deterministic algorithms. These results confirm that this algorithm is capable of delivering good performance in the experimental domain, including comparison against an alternative
978-1-4577-1104-6
406-411
Cai, Zhonglun
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Bristow, D.A.
1c924967-719f-471b-a200-4b73c8c8601e
Rogers, E.
990fd784-1526-448f-8d55-66685622831d
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Cai, Zhonglun
dd8dd525-19a5-4792-a048-617340996afe
Bristow, D.A.
1c924967-719f-471b-a200-4b73c8c8601e
Rogers, E.
990fd784-1526-448f-8d55-66685622831d
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815

Cai, Zhonglun, Bristow, D.A., Rogers, E. and Freeman, C.T. (2011) Experimental implementation of an iteration-varying optimal stochastic iterative learning control algorithm. 2011 IEEE International Symposium on Intelligent Control, United States. 28 - 30 Sep 2011. pp. 406-411 . (doi:10.1109/ISIC.2011.6045408).

Record type: Conference or Workshop Item (Other)

Abstract

A number of iterative learning control algorithms have been developed in a stochastic setting in recent years. The results currently available are in the form of fundamental systems theoretical properties and associated algorithm development. This paper reports results from the application of a stochastic algorithm on a gantry robot system that has been used in the benchmarking a range of deterministic algorithms. These results confirm that this algorithm is capable of delivering good performance in the experimental domain, including comparison against an alternative

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More information

Published date: September 2011
Venue - Dates: 2011 IEEE International Symposium on Intelligent Control, United States, 2011-09-28 - 2011-09-30
Organisations: Southampton Wireless Group, Aerodynamics & Flight Mechanics Group

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Local EPrints ID: 348077
URI: https://eprints.soton.ac.uk/id/eprint/348077
ISBN: 978-1-4577-1104-6
PURE UUID: 41236501-d40c-43e6-95d7-e03bc177e9cb

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Date deposited: 14 Feb 2013 14:27
Last modified: 03 Dec 2018 17:33

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Contributors

Author: Zhonglun Cai
Author: D.A. Bristow
Author: E. Rogers
Author: C.T. Freeman

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