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Generalized iterative learning control using successive projection: algorithm, convergence and experimental verification

Generalized iterative learning control using successive projection: algorithm, convergence and experimental verification
Generalized iterative learning control using successive projection: algorithm, convergence and experimental verification
Iterative learning control (ILC) is a high performance control design method for systems working in a repetitive manner. ILC has traditionally focused on tracking a reference defined at all points over a finite time interval; recent developments have begun to exploit the design freedom unlocked by tracking only a finite number of distinct time instants driven by the needs of e.g. robotic pick-and-place tasks. This paper proposes a generalized ILC paradigm which extends and unifies the scope of existing design frameworks by amalgamating previous task descriptions and embedding system constraints on the input and output. A novel solution is then derived using a successive projection method which provides well defined convergence properties. The proposed design framework is illustrated by applying it to a spatial reference tracking problem with experimental results on a gantry robot testing platform demonstrating its effectiveness.
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 (2019) Generalized iterative learning control using successive projection: algorithm, convergence and experimental verification. IEEE Transactions on Control Systems Technology. (In Press)

Record type: Article

Abstract

Iterative learning control (ILC) is a high performance control design method for systems working in a repetitive manner. ILC has traditionally focused on tracking a reference defined at all points over a finite time interval; recent developments have begun to exploit the design freedom unlocked by tracking only a finite number of distinct time instants driven by the needs of e.g. robotic pick-and-place tasks. This paper proposes a generalized ILC paradigm which extends and unifies the scope of existing design frameworks by amalgamating previous task descriptions and embedding system constraints on the input and output. A novel solution is then derived using a successive projection method which provides well defined convergence properties. The proposed design framework is illustrated by applying it to a spatial reference tracking problem with experimental results on a gantry robot testing platform demonstrating its effectiveness.

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Chen_IEEECST_accepted - Accepted Manuscript
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Accepted/In Press date: 3 July 2019

Identifiers

Local EPrints ID: 432354
URI: https://eprints.soton.ac.uk/id/eprint/432354
ISSN: 1063-6536
PURE UUID: a65ef196-b235-4c5e-85de-9e4db77d6c09
ORCID for Bing Chu: ORCID iD orcid.org/0000-0002-2711-8717

Catalogue record

Date deposited: 11 Jul 2019 16:30
Last modified: 05 Nov 2019 05:01

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Contributors

Author: Yiyang Chen
Author: Bing Chu ORCID iD
Author: Christopher Freeman

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