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 genetic algorithm controller shows the population converges to stable controllers. The controller is then employed to optimize the regulation of a ball-beam system. The dynamics of the ball-beam and the results of computer simulations of the control system are given in support of the developed theory. The genetic algorithm controller is shown to optimize the regulation of the ball-beam system in with respect to an LQR performance index.
| Original language | English |
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| Pages | 608-613 |
| Number of pages | 6 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 IEEE International Conference on Control Applications - Dearborn, MI, USA Duration: Sep 15 1996 → Sep 18 1996 |
Conference
| Conference | Proceedings of the 1996 IEEE International Conference on Control Applications |
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| City | Dearborn, MI, USA |
| Period | 9/15/96 → 9/18/96 |
ASJC Scopus subject areas
- Control and Systems Engineering