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Parameter-dependent Lyapunov function-based robust iterative learning control for discrete systems with actuator faults

Parameter-dependent Lyapunov function-based robust iterative learning control for discrete systems with actuator faults
Parameter-dependent Lyapunov function-based robust iterative learning control for discrete systems with actuator faults
This paper considers iterative learning control for a class of uncertain multiple-input multiple-output discrete linear systems with polytopic uncertainties and actuator faults. The stability theory for linear repetitive processes is used to develop control law design algorithms that can be computed using linear matrix inequalities. A class of parameter-dependent Lyapunov functions is used with the aim of enlarging the allowed polytopic uncertainty range for successful design. The effectiveness and feasibility of the new design algorithms are illustrated by a gantry robot case study.
actuator faults, iterative learning control, polytopic uncertainty, linear matrix inequalities
0890-6327
1-19
Ding, J.
3c8f054d-a84e-4f16-9767-c76364a1b5a2
Galkowski, K.
40c02cf5-8fcb-44de-bb1e-f9f70fdd265d
Cichy, B.
3473093e-3203-4acf-b06f-5dc999fac942
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Yang, H.
c0c036ca-374c-4c71-84a5-89ce439a7e3e
Ding, J.
3c8f054d-a84e-4f16-9767-c76364a1b5a2
Galkowski, K.
40c02cf5-8fcb-44de-bb1e-f9f70fdd265d
Cichy, B.
3473093e-3203-4acf-b06f-5dc999fac942
Rogers, E.
611b1de0-c505-472e-a03f-c5294c63bb72
Yang, H.
c0c036ca-374c-4c71-84a5-89ce439a7e3e

Ding, J., Galkowski, K., Cichy, B., Rogers, E. and Yang, H. (2016) Parameter-dependent Lyapunov function-based robust iterative learning control for discrete systems with actuator faults. International Journal of Adaptive Control and Signal Processing, 1-19. (doi:10.1002/acs.2684).

Record type: Article

Abstract

This paper considers iterative learning control for a class of uncertain multiple-input multiple-output discrete linear systems with polytopic uncertainties and actuator faults. The stability theory for linear repetitive processes is used to develop control law design algorithms that can be computed using linear matrix inequalities. A class of parameter-dependent Lyapunov functions is used with the aim of enlarging the allowed polytopic uncertainty range for successful design. The effectiveness and feasibility of the new design algorithms are illustrated by a gantry robot case study.

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More information

Accepted/In Press date: 4 March 2016
e-pub ahead of print date: 29 March 2016
Keywords: actuator faults, iterative learning control, polytopic uncertainty, linear matrix inequalities

Identifiers

Local EPrints ID: 392889
URI: http://eprints.soton.ac.uk/id/eprint/392889
ISSN: 0890-6327
PURE UUID: 0a1c6400-ef0b-4abd-9f95-76920b638ff4
ORCID for E. Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 17 Apr 2016 14:39
Last modified: 07 Oct 2020 06:22

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