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LMI-based gain scheduled ILC design for linear parameter-varying systems

LMI-based gain scheduled ILC design for linear parameter-varying systems
LMI-based gain scheduled ILC design for linear parameter-varying systems
This paper considers the design of iterative learning control laws for systems whose state-space model matrices are functions of a vector of varying parameters. The repetitive process setting is exploited to develop a linear matrix inequality based procedure for computing gain-scheduling feedback and feedforward (learning) controllers. These controllers guarantee acceptable dynamics along the trials and ensure monotonic convergence of the trial-to-trial error dynamics, respectively. A simulation example is given to illustrate the theoretical developments.
Paszke, W.
dd4b8f12-17c7-45ee-bfb0-e9675bd7d854
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Galkowski, K.
40c02cf5-8fcb-44de-bb1e-f9f70fdd265d
Paszke, W.
dd4b8f12-17c7-45ee-bfb0-e9675bd7d854
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Galkowski, K.
40c02cf5-8fcb-44de-bb1e-f9f70fdd265d

Paszke, W., Rogers, E. and Galkowski, K. (2016) LMI-based gain scheduled ILC design for linear parameter-varying systems. 2016 American Control Conference, ACC 2016, United States. 05 - 07 Jul 2016. 6 pp . (doi:10.1109/ACC.2016.7524943).

Record type: Conference or Workshop Item (Paper)

Abstract

This paper considers the design of iterative learning control laws for systems whose state-space model matrices are functions of a vector of varying parameters. The repetitive process setting is exploited to develop a linear matrix inequality based procedure for computing gain-scheduling feedback and feedforward (learning) controllers. These controllers guarantee acceptable dynamics along the trials and ensure monotonic convergence of the trial-to-trial error dynamics, respectively. A simulation example is given to illustrate the theoretical developments.

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More information

e-pub ahead of print date: 1 August 2016
Venue - Dates: 2016 American Control Conference, ACC 2016, United States, 2016-07-05 - 2016-07-07
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 386834
URI: http://eprints.soton.ac.uk/id/eprint/386834
PURE UUID: 5a1190de-a1b6-4e49-8063-6c46fc2496e2
ORCID for E. Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 02 Feb 2016 20:35
Last modified: 10 Sep 2020 01:31

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