A comparative study of genetic operators for controller parameter optimisation

Alfaro-Cid, E., McGookin, E.W. and Murray-Smith, D.J. (2009) A comparative study of genetic operators for controller parameter optimisation. Control Engineering Practice, 17(1), pp. 185-197. (doi:10.1016/j.conengprac.2008.06.001)

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Publisher's URL: http://dx.doi.org/10.1016/j.conengprac.2008.06.001

Abstract

The objective of this paper is to propose a genetic algorithm (GA) scheme that works well in a spectrum of controller parameter optimisation problems. A set of 18 different GAs, which combine three different selection methods, three probabilities of crossover and two probabilities of mutation, are used to solve four controller parameter optimisation problems and the results obtained are compared. in each of these problems the control methodology varies so the study covers a variety of current control research areas.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Murray-Smith, Professor David and McGookin, Dr Euan
Authors: Alfaro-Cid, E., McGookin, E.W., and Murray-Smith, D.J.
College/School:College of Science and Engineering > School of Engineering > Aerospace Sciences
Journal Name:Control Engineering Practice
ISSN:0967-0661

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