Genetic control of a ball-beam system

Author

Marra, M.A. ; Boling, B.E. ; Walcott, B.L.

Author_Institution

Dept. of Electr. Eng., Kentucky Univ., Lexington, KY, USA

fYear

1996

fDate

15-18 Sep 1996

Firstpage

608

Lastpage

613

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

Keywords

adaptive control; genetic algorithms; linear quadratic control; optimisation; stability; LQR performance index; adaptive system control; ball-beam system; genetic algorithms; genetic control; optimum controller; probabilistic genetic operators; stability; Adaptive control; Adaptive systems; Algorithm design and analysis; Computer simulation; Control system synthesis; Control systems; Genetic algorithms; Performance analysis; Programmable control; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Applications, 1996., Proceedings of the 1996 IEEE International Conference on

Conference_Location

Dearborn, MI

Print_ISBN

0-7803-2975-9

Type

conf

DOI

10.1109/CCA.1996.558930

Filename

558930