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Norm Optimal Iterative Learning Control for Planar Tracking Tasks

Norm Optimal Iterative Learning Control for Planar Tracking Tasks
Norm Optimal Iterative Learning Control for Planar Tracking Tasks
The Iterative Learning Control (ILC) problem in which tracking is only required at a subset of isolated time points along the trial duration has recently gained significant attention since it addresses the practical needs of many applications. This paper extends the framework by embedding simultaneous iterative convergence of subsets of outputs to reference trajectories on subintervals. This enables it to tackle tasks which mix 'point to point' movements with linear tracking requirements, which substantially broadens the application domain (e.g. to include automation tasks which include welding or cutting movements, or human motion control where the movement is restricted by the task to straight line and/or planar segments). A solution to the problem is presented in the framework of Norm Optimal ILC (NOILC), providing well-defined convergence properties, design guidelines and supporting experimental results.
683-688
Owens, D.H.
3452e9bb-d3bd-4995-b4bb-424bbd288b09
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Chu, B.
555a86a5-0198-4242-8525-3492349d4f0f
Owens, D.H.
3452e9bb-d3bd-4995-b4bb-424bbd288b09
Freeman, C.T.
ccdd1272-cdc7-43fb-a1bb-b1ef0bdf5815
Chu, B.
555a86a5-0198-4242-8525-3492349d4f0f

Owens, D.H., Freeman, C.T. and Chu, B. (2013) Norm Optimal Iterative Learning Control for Planar Tracking Tasks. IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, France. pp. 683-688 .

Record type: Conference or Workshop Item (Paper)

Abstract

The Iterative Learning Control (ILC) problem in which tracking is only required at a subset of isolated time points along the trial duration has recently gained significant attention since it addresses the practical needs of many applications. This paper extends the framework by embedding simultaneous iterative convergence of subsets of outputs to reference trajectories on subintervals. This enables it to tackle tasks which mix 'point to point' movements with linear tracking requirements, which substantially broadens the application domain (e.g. to include automation tasks which include welding or cutting movements, or human motion control where the movement is restricted by the task to straight line and/or planar segments). A solution to the problem is presented in the framework of Norm Optimal ILC (NOILC), providing well-defined convergence properties, design guidelines and supporting experimental results.

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More information

Published date: 3 July 2013
Venue - Dates: IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, France, 2013-07-03
Organisations: EEE, Southampton Wireless Group

Identifiers

Local EPrints ID: 347877
URI: http://eprints.soton.ac.uk/id/eprint/347877
PURE UUID: 5e583f1b-d41e-494a-966b-826ef32b751a
ORCID for B. Chu: ORCID iD orcid.org/0000-0002-2711-8717

Catalogue record

Date deposited: 31 Jan 2013 22:31
Last modified: 20 Jul 2019 00:42

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Contributors

Author: D.H. Owens
Author: C.T. Freeman
Author: B. Chu ORCID iD

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