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Experimental evaluation of iterative learning control algorithms for non-minimum phase plants

Experimental evaluation of iterative learning control algorithms for non-minimum phase plants
Experimental evaluation of iterative learning control algorithms for non-minimum phase plants
The purpose of this paper is two-fold, firstly it describes the development and modelling of an experimental test facility as a platform on which to assess the performance of Iterative Learning Control (ILC) schemes. This facility includes a non-minimum phase component. Secondly, P-Type, D-Type and phase-lead types of the algorithm have been implemented on the test-bed, results are presented for each method and their performance is compared. Although all the ILC strategies tested experience eventual divergence when applied to a non-minimum phase system, it is found that there is an optimum phase-lead ILC design that maximizes convergence and minimizes error. A general method of arriving at this phase-lead from knowledge of the plant model is described. A variety of filters have been applied and assessed in order to improve the overall performance of the algorithm.
0020-3270
826-846
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72

Freeman, C.T., Lewin, P.L. and Rogers, E. (2005) Experimental evaluation of iterative learning control algorithms for non-minimum phase plants. International Journal of Control, 78 (11), 826-846.

Record type: Article

Abstract

The purpose of this paper is two-fold, firstly it describes the development and modelling of an experimental test facility as a platform on which to assess the performance of Iterative Learning Control (ILC) schemes. This facility includes a non-minimum phase component. Secondly, P-Type, D-Type and phase-lead types of the algorithm have been implemented on the test-bed, results are presented for each method and their performance is compared. Although all the ILC strategies tested experience eventual divergence when applied to a non-minimum phase system, it is found that there is an optimum phase-lead ILC design that maximizes convergence and minimizes error. A general method of arriving at this phase-lead from knowledge of the plant model is described. A variety of filters have been applied and assessed in order to improve the overall performance of the algorithm.

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Published date: July 2005
Organisations: EEE, Southampton Wireless Group

Identifiers

Local EPrints ID: 260545
URI: https://eprints.soton.ac.uk/id/eprint/260545
ISSN: 0020-3270
PURE UUID: 4ea29900-fd82-4d0e-94f4-9fa7edc62972

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Date deposited: 17 Feb 2005
Last modified: 10 Nov 2017 15:39

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Contributors

Author: C.T. Freeman
Author: P.L. Lewin
Author: E. Rogers

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