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 algorithms controllers, and addresses the key issue of stability. A theoretical analysis of the proposed genetic algorithm controller shows the population converges to stable controllers under fitness-proportionate selection pressure. The minimization of the effects of instability is also discussed.
|Number of pages||4|
|Journal||Conference Proceedings - IEEE SOUTHEASTCON|
|State||Published - 1996|
|Event||Proceedings of the 1996 IEEE SOUTHEASTCON Conference - Tampa, FL, USA|
Duration: Apr 11 1996 → Apr 14 1996
ASJC Scopus subject areas
- Electrical and Electronic Engineering