Point-to-point iterative learning control with optimal tracking time allocation: a coordinate descent approach
Point-to-point iterative learning control with optimal tracking time allocation: a coordinate descent approach
Iterative learning control (ILC) is a high performance control technique for systems operating in a repetitive manner. A novel design methodology is developed in this paper to incorporate optimal tracking time allocation within the point-to-point ILC framework for discrete time systems. This leads to significant performance improvements compared to fixed time points (e.g. energy reduction). An optimization problem is formulated based on the point-to-point tracking requirement and the via-point temporal constraints. A two stage design framework is proposed to solve this problem, yielding an algorithm based on norm optimal ILC and the coordinate descent method, which automatically minimizes control effort while maintaining high performance tracking. The proposed algorithm is implemented on a gantry robot experimental test platform, with results verifying its practical effectiveness in the presence of model uncertainty.
3298-3303
Chen, Yiyang
2633396c-fcb8-4b50-8104-3d0da5d734cc
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Freeman, Christopher
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
2017
Chen, Yiyang
2633396c-fcb8-4b50-8104-3d0da5d734cc
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: a coordinate descent approach.
In 2017 36th Chinese Control Conference (CCC).
IEEE.
.
(doi:10.23919/ChiCC.2017.8027867).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Iterative learning control (ILC) is a high performance control technique for systems operating in a repetitive manner. A novel design methodology is developed in this paper to incorporate optimal tracking time allocation within the point-to-point ILC framework for discrete time systems. This leads to significant performance improvements compared to fixed time points (e.g. energy reduction). An optimization problem is formulated based on the point-to-point tracking requirement and the via-point temporal constraints. A two stage design framework is proposed to solve this problem, yielding an algorithm based on norm optimal ILC and the coordinate descent method, which automatically minimizes control effort while maintaining high performance tracking. The proposed algorithm is implemented on a gantry robot experimental test platform, with results verifying its practical effectiveness in the presence of model uncertainty.
Text
CCC_Chen_Chu_Freeman_2017.pdf
- Accepted Manuscript
More information
Submitted date: 7 December 2016
Accepted/In Press date: 1 February 2017
e-pub ahead of print date: 11 September 2017
Published date: 2017
Venue - Dates:
36th Chinese Control Conference (CCC), , Dalian, China, 2017-07-26 - 2017-07-28
Organisations:
Vision, Learning and Control, EEE
Identifiers
Local EPrints ID: 403684
URI: http://eprints.soton.ac.uk/id/eprint/403684
ISSN: 1934-1768
PURE UUID: ba8c9372-9d5d-49c3-b118-e00efe9ee354
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Date deposited: 07 Dec 2016 17:54
Last modified: 16 Mar 2024 04:10
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Contributors
Author:
Yiyang Chen
Author:
Bing Chu
Author:
Christopher Freeman
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