A 2D Systems Approach to Iterative Learning Control for Discrete Linear Processes with Zero First Markov Parameter
A 2D Systems Approach to Iterative Learning Control for Discrete Linear Processes with Zero First Markov Parameter
In this paper we develop a new approach to iterative learning control for the practically relevant case of deterministic discrete linear plants where the first Markov parameter is zero. The basis for this is a 2D systems approach that, by using a strong form of stability for linear repetitive processes, also allows us to consider both trial-to-trial and along the trial performance. This is in contrast to many other approaches where the sole emphasis is on error convergence. The resulting design computations are in terms of Linear Matrix Inequalities (LMIs). Results from experimentally applying the resulting control law to one axis of a gantry robot are also given.
Hladowski, Lukasz
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Galkowski, Krzysztof
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Cai, Zhonglun
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Rogers, Eric
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Freeman, Christopher
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Lewin, Paul
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14 December 2009
Hladowski, Lukasz
db41c3fd-6c9e-48e8-81e7-9613072c59b5
Galkowski, Krzysztof
322994ac-7e24-4350-ab72-cc80ac8078ef
Cai, Zhonglun
dd8dd525-19a5-4792-a048-617340996afe
Rogers, Eric
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Freeman, Christopher
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Lewin, Paul
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Hladowski, Lukasz, Galkowski, Krzysztof, Cai, Zhonglun, Rogers, Eric, Freeman, Christopher and Lewin, Paul
(2009)
A 2D Systems Approach to Iterative Learning Control for Discrete Linear Processes with Zero First Markov Parameter.
Symposium on Learning Control at IEEE CDC 2009, Shanghai.
14 - 15 Dec 2009.
Record type:
Conference or Workshop Item
(Paper)
Abstract
In this paper we develop a new approach to iterative learning control for the practically relevant case of deterministic discrete linear plants where the first Markov parameter is zero. The basis for this is a 2D systems approach that, by using a strong form of stability for linear repetitive processes, also allows us to consider both trial-to-trial and along the trial performance. This is in contrast to many other approaches where the sole emphasis is on error convergence. The resulting design computations are in terms of Linear Matrix Inequalities (LMIs). Results from experimentally applying the resulting control law to one axis of a gantry robot are also given.
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Published date: 14 December 2009
Additional Information:
Event Dates: December 14-15, 2009
Venue - Dates:
Symposium on Learning Control at IEEE CDC 2009, Shanghai, 2009-12-14 - 2009-12-15
Organisations:
EEE, Southampton Wireless Group
Identifiers
Local EPrints ID: 266859
URI: http://eprints.soton.ac.uk/id/eprint/266859
PURE UUID: b0b0dd44-50ad-4b4c-b18c-f14e63a14315
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Date deposited: 04 Nov 2008 11:16
Last modified: 15 Mar 2024 02:43
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Contributors
Author:
Lukasz Hladowski
Author:
Krzysztof Galkowski
Author:
Zhonglun Cai
Author:
Eric Rogers
Author:
Christopher Freeman
Author:
Paul Lewin
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