A comparative study of genetic operators for controller parameter optimisation

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.