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Parameter optimal iterative learning control using polynomial representations of the inverse plant

Parameter optimal iterative learning control using polynomial representations of the inverse plant
Parameter optimal iterative learning control using polynomial representations of the inverse plant
Based on the observation that iterative learning control (ILC) can be based on the inverse plant but that the approach can be degraded by modelling errors, particularly at high frequencies, this article investigates the construction and properties of a multi-parameter parameter-optimal ILC algorithm that uses an approximate polynomial representation of the inverse with natural high-frequency attenuation. In its simplest form, the algorithm replicates the original work of Owens and Feng but, more generally, it is capable of producing significant improvements to the observed convergence rate. As the number of parameters increases, convergence rates approach that of the ideal plant inverse algorithm. Introducing compensation into the algorithm provides a formal link to previously published gradient and norm-optimal ILC algorithms and indicates that the polynomial approach can be regarded as approximations to those control laws. Simulation examples verify the theoretical performance predictions.
0020-3270
Owens, David
0d0eb9da-c362-457d-841f-3094a18120ee
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Songjun, Mutita
e2e1042a-9d28-4abb-a279-487facf07e73
Owens, David
0d0eb9da-c362-457d-841f-3094a18120ee
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Songjun, Mutita
e2e1042a-9d28-4abb-a279-487facf07e73

Owens, David, Chu, Bing and Songjun, Mutita (2012) Parameter optimal iterative learning control using polynomial representations of the inverse plant. International Journal of Control. (doi:10.1080/00207179.2012.658867).

Record type: Article

Abstract

Based on the observation that iterative learning control (ILC) can be based on the inverse plant but that the approach can be degraded by modelling errors, particularly at high frequencies, this article investigates the construction and properties of a multi-parameter parameter-optimal ILC algorithm that uses an approximate polynomial representation of the inverse with natural high-frequency attenuation. In its simplest form, the algorithm replicates the original work of Owens and Feng but, more generally, it is capable of producing significant improvements to the observed convergence rate. As the number of parameters increases, convergence rates approach that of the ideal plant inverse algorithm. Introducing compensation into the algorithm provides a formal link to previously published gradient and norm-optimal ILC algorithms and indicates that the polynomial approach can be regarded as approximations to those control laws. Simulation examples verify the theoretical performance predictions.

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More information

e-pub ahead of print date: 13 February 2012
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 336253
URI: http://eprints.soton.ac.uk/id/eprint/336253
ISSN: 0020-3270
PURE UUID: 284ed39d-354d-4305-ae83-0435a9c73939
ORCID for Bing Chu: ORCID iD orcid.org/0000-0002-2711-8717

Catalogue record

Date deposited: 20 Mar 2012 12:23
Last modified: 28 Apr 2022 02:06

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Contributors

Author: David Owens
Author: Bing Chu ORCID iD
Author: Mutita Songjun

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