Stability analysis of genetic algorithm controllers

Abstract

This study presents a method of adaptive system control based on genetic algorithms. The method consists of a population of controllers evolving towards an optimum controller through the use of probabilistic genetic operators. A brief overview of genetic algorithms is first given. The remainder of the paper identifies the problems associated with genetic algorithm controllers, and addresses the key issue of stability. A theoretical analysis of the proposed genetic algorithm controller shows that the population converges to stable controllers under fitness-proportionate selection pressure. The minimization of the effects of instability is also discussed.