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2D systems based robust iterative learning control using noncausal finite-time interval data

Cichy, B, Galkowski, K and Rogers, E (2014) 2D systems based robust iterative learning control using noncausal finite-time interval data. Systems & Control Letters, 64, 36-42.

Record type: Article

Abstract

This paper uses a $2$D systems setting in the form of repetitive process stability theory to design an iterative learning control law that is robust against model uncertainty. In iterative learning control the same finite duration operation, known as a trial over the trial length, is performed over and over again with resetting to the starting location once each is complete, or a stoppage at the end of the current trial before the next one begins. The basic idea of this form of control is to use information from the previous trial, or a finite number thereof, to compute the control input for the next trial. At any instant on the current trial, data from the complete previous trial is available and hence noncausal information in the trial length indeterminate can be used. This paper also shows how the new $2$D systems based design algorithms enable the effective deployment of such information.

Text
scl2014.pdf - Other

Accepted/In Press date: 6 November 2013
e-pub ahead of print date: 14 December 2013
Published date: February 2014
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 361925
URI: http://eprints.soton.ac.uk/id/eprint/361925
PURE UUID: 2ece3177-9dc0-4fca-9d71-ee0a6bb5b01b
ORCID for E Rogers: orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 05 Feb 2014 20:03

Contributors

Author: B Cichy
Author: K Galkowski
Author: E Rogers