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Iterative learning control of repetitive transverse loads in elastic materials

Iterative learning control of repetitive transverse loads in elastic materials
Iterative learning control of repetitive transverse loads in elastic materials

This paper develops a computational scheme to solve the optimal tracking control problem by repeated trials for distributed-parameter processes where an example from elasticity analysis in structural mechanics is used as motivation. An adaptive control scheme based on iterative learning control is used to develop an effective solution of underlying optimization task. The essential feature of the resulting approach is the efficient modelling and simulation of the distributed system under consideration using discretization based on the finite element method. Also to reduce the uncertainty of the model used for the control design, thus increasing the system performance, the iterative learning control scheme is extended by parameter estimation of mathematical model through application of one form of sequential experimental design. The related sensor location problem corresponds to situation where from among all potential sites where the sensors can be placed a subset must be selected that provide the most informative measurements to update the system parameter estimates. The new results are lustrated by an example from the area of smart materials.

2576-2370
5270-5275
IEEE
Patan, Maciej
06a9c509-e4e0-43fc-a70e-04af0c8a4c59
Patan, Krzysztof
ed81c4e0-a3b1-4e42-b0aa-361721ac6fbe
Galkowski, Krzysztof
ce0d0509-675e-4d30-b2c4-2ca46c22dbe5
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
Patan, Maciej
06a9c509-e4e0-43fc-a70e-04af0c8a4c59
Patan, Krzysztof
ed81c4e0-a3b1-4e42-b0aa-361721ac6fbe
Galkowski, Krzysztof
ce0d0509-675e-4d30-b2c4-2ca46c22dbe5
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72

Patan, Maciej, Patan, Krzysztof, Galkowski, Krzysztof and Rogers, Eric (2019) Iterative learning control of repetitive transverse loads in elastic materials. In 2018 IEEE Conference on Decision and Control, CDC 2018. vol. 2018-December, IEEE. pp. 5270-5275 . (doi:10.1109/CDC.2018.8619699).

Record type: Conference or Workshop Item (Paper)

Abstract

This paper develops a computational scheme to solve the optimal tracking control problem by repeated trials for distributed-parameter processes where an example from elasticity analysis in structural mechanics is used as motivation. An adaptive control scheme based on iterative learning control is used to develop an effective solution of underlying optimization task. The essential feature of the resulting approach is the efficient modelling and simulation of the distributed system under consideration using discretization based on the finite element method. Also to reduce the uncertainty of the model used for the control design, thus increasing the system performance, the iterative learning control scheme is extended by parameter estimation of mathematical model through application of one form of sequential experimental design. The related sensor location problem corresponds to situation where from among all potential sites where the sensors can be placed a subset must be selected that provide the most informative measurements to update the system parameter estimates. The new results are lustrated by an example from the area of smart materials.

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More information

Published date: 21 January 2019
Venue - Dates: 57th IEEE Conference on Decision and Control, CDC 2018, United States, 2018-12-17 - 2018-12-19

Identifiers

Local EPrints ID: 429149
URI: http://eprints.soton.ac.uk/id/eprint/429149
ISSN: 2576-2370
PURE UUID: 2ce69e01-8768-4d86-ab66-1c91b20ea54d
ORCID for Eric Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 22 Mar 2019 17:30
Last modified: 27 Jan 2020 13:34

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Contributors

Author: Maciej Patan
Author: Krzysztof Patan
Author: Krzysztof Galkowski
Author: Eric Rogers ORCID iD

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