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 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.
| Original language | English |
|---|---|
| Pages (from-to) | 204-207 |
| 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