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Analysis of Linear Iterative Learning Control Schemes Using Repetitive Process Theory

Analysis of Linear Iterative Learning Control Schemes Using Repetitive Process Theory
Analysis of Linear Iterative Learning Control Schemes Using Repetitive Process Theory
The purposes of this paper are to (i) critically review existing results on the use of the systems theory for repetitive process in the analysis of a wide class of linear iterative control laws, and (ii) to present some new results on controller design using this general approach. This paper first presents results on the stability and convergence properties of a general class of iterative learning control schemes using, in the main, theory first developed for the sub-class of differential and discrete linear repetitive processes. A general learning law that uses information from the current and a finite number of previous trials is considered and the results, in the form of fundamental limitations on the benefits of using this law, are interpreted in terms of basic systems theoretic concepts such as the relative degree and minimum phase characteristics. It is also shown that a number of other approaches reported in the literature are, in fact, special cases of the results obtained in the repetitive process setting. In the second part of the paper, new results on controller design are given based on 2D transfer function matrices together with new results on the robustness of predictive optimal control schemes (a form of predictive control for linear repetitive processes).
68-91
Owens, D H
db24b8ef-282b-47c0-9cd2-75e91d312ad7
Rogers, E
611b1de0-c505-472e-a03f-c5294c63bb72
Moore, K L
54e8a34b-6d45-4ac9-9e68-120c62c72a55
Owens, D H
db24b8ef-282b-47c0-9cd2-75e91d312ad7
Rogers, E
611b1de0-c505-472e-a03f-c5294c63bb72
Moore, K L
54e8a34b-6d45-4ac9-9e68-120c62c72a55

Owens, D H, Rogers, E and Moore, K L (2002) Analysis of Linear Iterative Learning Control Schemes Using Repetitive Process Theory. Asian Journal of Control, 4 (1), 68-91.

Record type: Article

Abstract

The purposes of this paper are to (i) critically review existing results on the use of the systems theory for repetitive process in the analysis of a wide class of linear iterative control laws, and (ii) to present some new results on controller design using this general approach. This paper first presents results on the stability and convergence properties of a general class of iterative learning control schemes using, in the main, theory first developed for the sub-class of differential and discrete linear repetitive processes. A general learning law that uses information from the current and a finite number of previous trials is considered and the results, in the form of fundamental limitations on the benefits of using this law, are interpreted in terms of basic systems theoretic concepts such as the relative degree and minimum phase characteristics. It is also shown that a number of other approaches reported in the literature are, in fact, special cases of the results obtained in the repetitive process setting. In the second part of the paper, new results on controller design are given based on 2D transfer function matrices together with new results on the robustness of predictive optimal control schemes (a form of predictive control for linear repetitive processes).

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More information

Published date: 2002
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 254274
URI: http://eprints.soton.ac.uk/id/eprint/254274
PURE UUID: 0dfad365-2419-4214-add5-792abb8a693f
ORCID for E Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 01 Mar 2004
Last modified: 18 Oct 2022 01:33

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Contributors

Author: D H Owens
Author: E Rogers ORCID iD
Author: K L Moore

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