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The influence of non-minimum phase zeros on the performance of optimal continuous-time iterative learning control

The influence of non-minimum phase zeros on the performance of optimal continuous-time iterative learning control
The influence of non-minimum phase zeros on the performance of optimal continuous-time iterative learning control
Iterative learning control can be applied to systems that execute the same tracking task over a finite time duration. An execution is known as a trial, and once each is complete the system resets to the starting location and the next trial begins. All previous trial information is available for use in constructing the control input for the next trial, and the basic idea is to improve tracking performance from trial-to-trial. This paper analyzes the effects of non-minimum phase zeros on the trial-to-trial error norm convergence of norm optimal iterative learning control, a commonly used algorithm, for differential linear systems with supporting experimental results from a test facility
1063-6536
1151-1158
Owens, D.H.
3452e9bb-d3bd-4995-b4bb-424bbd288b09
Chu, B.
555a86a5-0198-4242-8525-3492349d4f0f
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Owens, D.H.
3452e9bb-d3bd-4995-b4bb-424bbd288b09
Chu, B.
555a86a5-0198-4242-8525-3492349d4f0f
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e

Owens, D.H., Chu, B., Rogers, E., Freeman, C.T. and Lewin, P.L. (2014) The influence of non-minimum phase zeros on the performance of optimal continuous-time iterative learning control. IEEE Transactions on Control Systems Technology, 22 (3), 1151-1158. (doi:10.1109/TCST.2013.2267743).

Record type: Article

Abstract

Iterative learning control can be applied to systems that execute the same tracking task over a finite time duration. An execution is known as a trial, and once each is complete the system resets to the starting location and the next trial begins. All previous trial information is available for use in constructing the control input for the next trial, and the basic idea is to improve tracking performance from trial-to-trial. This paper analyzes the effects of non-minimum phase zeros on the trial-to-trial error norm convergence of norm optimal iterative learning control, a commonly used algorithm, for differential linear systems with supporting experimental results from a test facility

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Accepted/In Press date: 8 June 2013
e-pub ahead of print date: 28 June 2013
Published date: 2014
Organisations: EEE, Southampton Wireless Group

Identifiers

Local EPrints ID: 352098
URI: http://eprints.soton.ac.uk/id/eprint/352098
ISSN: 1063-6536
PURE UUID: f8c48050-8f44-451f-8882-3df0666132ab
ORCID for B. Chu: ORCID iD orcid.org/0000-0002-2711-8717
ORCID for E. Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 02 May 2013 10:20
Last modified: 26 Nov 2019 02:05

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Contributors

Author: D.H. Owens
Author: B. Chu ORCID iD
Author: E. Rogers ORCID iD
Author: C.T. Freeman
Author: P.L. Lewin

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