Limit sets and switching strategies in parameter-optimal iterative learning control


Owens, D. H., Tomas-Rodriguez, M. and Daley, S. (2008) Limit sets and switching strategies in parameter-optimal iterative learning control. International Journal of Control, 81, (4), 626-640. (doi:10.1080/00207170701579403).

Download

Full text not available from this repository.

Description/Abstract

This paper characterizes the existence and form of the possible limit error signals in typical parameter-optimal iterative learning control. The set of limit errors has attracting and repelling components and the behaviour of the algorithm in the vicinity of these sets can be associated with the undesirable properties of apparent (but in fact temporary) convergence or permanent slow convergence properties in practice. The avoidance of these behaviours in practice is investigated using novel switching strategies. Deterministic strategies are analysed to prove the feasibility of the concept by proving that each of a number of such strategies is guaranteed to produce global convergence of errors to zero independent of the details of plant dynamics. For practical applications a random switching strategy is proposed to replace these approaches and shown, by example, to produce substantial potential improvements when compared with the non-switching case. The work described in this paper is covered by pending patent applications in the UK and elsewhere.

Item Type: Article
ISSNs: 0020-7179 (print)
1366-5820 (electronic)
Related URLs:
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering and the Environment > Institute of Sound and Vibration Research > Signal Processing & Control Research Group
ePrint ID: 334372
Date Deposited: 07 Mar 2012 16:32
Last Modified: 27 Mar 2014 20:19
URI: http://eprints.soton.ac.uk/id/eprint/334372

Actions (login required)

View Item View Item