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Point-to-point iterative learning control with optimal tracking time allocation

Point-to-point iterative learning control with optimal tracking time allocation
Point-to-point iterative learning control with optimal tracking time allocation
Iterative learning control is a high performance tracking control design method for systems operating in a repetitive manner. This paper proposes a novel design methodology that extends the recently developed point-to-point iterative learning control framework to allow automatic via-point time allocation within a given point-to-point tracking task, leading to significant performance improvements, e.g. energy reduction. The problem is formulated into an optimization framework with via-point temporal constraints and a reference tracking requirement, for which a two stage design approach is developed. This yields an algorithmic solution which minimizes input energy based on norm optimal iterative learning control and gradient minimization. The algorithm is further expanded to incorporate system constraints into the design, prior to experimental validation on a gantry robot test platform to confirm its feasibility in practical applications.
1063-6536
Chen, Yiyang
da753778-ba38-4f95-ad29-b78ff9b12b05
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Chen, Yiyang
da753778-ba38-4f95-ad29-b78ff9b12b05
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815

Chen, Yiyang, Chu, Bing and Freeman, Christopher (2017) Point-to-point iterative learning control with optimal tracking time allocation. IEEE Transactions on Control Systems Technology. (In Press)

Record type: Article

Abstract

Iterative learning control is a high performance tracking control design method for systems operating in a repetitive manner. This paper proposes a novel design methodology that extends the recently developed point-to-point iterative learning control framework to allow automatic via-point time allocation within a given point-to-point tracking task, leading to significant performance improvements, e.g. energy reduction. The problem is formulated into an optimization framework with via-point temporal constraints and a reference tracking requirement, for which a two stage design approach is developed. This yields an algorithmic solution which minimizes input energy based on norm optimal iterative learning control and gradient minimization. The algorithm is further expanded to incorporate system constraints into the design, prior to experimental validation on a gantry robot test platform to confirm its feasibility in practical applications.

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More information

Submitted date: 1 August 2016
Accepted/In Press date: 3 April 2017
Organisations: Vision, Learning and Control, EEE

Identifiers

Local EPrints ID: 401028
URI: https://eprints.soton.ac.uk/id/eprint/401028
ISSN: 1063-6536
PURE UUID: 64512ffe-a8ba-40f9-a278-49d0c709da1e
ORCID for Bing Chu: ORCID iD orcid.org/0000-0002-2711-8717

Catalogue record

Date deposited: 01 Oct 2016 13:29
Last modified: 06 Jun 2018 12:29

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