Stability analysis of genetic algorithm controllers

Michael A. Marra, Brian E. Boling, Bruce L. Walcott

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


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 languageEnglish
Pages (from-to)204-207
Number of pages4
JournalConference Proceedings - IEEE SOUTHEASTCON
StatePublished - 1996
EventProceedings of the 1996 IEEE SOUTHEASTCON Conference - Tampa, FL, USA
Duration: Apr 11 1996Apr 14 1996

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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