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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
This paper proposes a novel design methodology that embeds optimal tracking time allocation within the point-to-point iterative learning control framework, thereby enabling significant reduction in the input energy required to follow a given point-to-point motion trajectory. The problem is formulated into an optimisation framework for which a two stage design approach is developed based on gradient method minimisation. Experimental results from a practical implementation of the proposed methodology using a gantry robot experimental test platform demonstrate its effectiveness.
0743-1546
6089-6094
IEEE
Chen, Yiyang
2633396c-fcb8-4b50-8104-3d0da5d734cc
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Freeman, Christopher T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Chen, Yiyang
2633396c-fcb8-4b50-8104-3d0da5d734cc
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Freeman, Christopher T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815

Chen, Yiyang, Chu, Bing and Freeman, Christopher T. (2015) Point-to-point iterative learning control with optimal tracking time allocation. In 2015 54th IEEE Conference on Decision and Control (CDC). IEEE. pp. 6089-6094 . (doi:10.1109/CDC.2015.7403177).

Record type: Conference or Workshop Item (Paper)

Abstract

This paper proposes a novel design methodology that embeds optimal tracking time allocation within the point-to-point iterative learning control framework, thereby enabling significant reduction in the input energy required to follow a given point-to-point motion trajectory. The problem is formulated into an optimisation framework for which a two stage design approach is developed based on gradient method minimisation. Experimental results from a practical implementation of the proposed methodology using a gantry robot experimental test platform demonstrate its effectiveness.

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More information

Published date: December 2015
Venue - Dates: 54th IEEE Conference on Decision and Control (CDC), Osaka, Japan, 2015-12-15 - 2015-12-18

Identifiers

Local EPrints ID: 429381
URI: https://eprints.soton.ac.uk/id/eprint/429381
ISSN: 0743-1546
PURE UUID: 394e3b5b-3305-4330-bc9e-ef21926e8465
ORCID for Yiyang Chen: ORCID iD orcid.org/0000-0001-9960-9040
ORCID for Bing Chu: ORCID iD orcid.org/0000-0002-2711-8717

Catalogue record

Date deposited: 27 Mar 2019 17:30
Last modified: 26 Jun 2019 00:32

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