GA-optimized fuzzy controller for spacecraft attitude control

Author

Satyadas, Antony ; KrishnaKumar, K.

Author_Institution

Alabama Univ., Tuscaloosa, AL, USA

fYear

1994

fDate

26-29 Jun 1994

Firstpage

1979

Abstract

Spacecraft attitude control is approached as a nonlinear control problem, the robustness quality of the genetic algorithm (GA)-optimized fuzzy logic (FL) control is demonstrated using a nonlinear model of the Space Station Freedom. The main components of the GA-optimized fuzzy controller (GAoFC) are the GA adaptive learning module, the objective function module, and the FC (fuzzy control) module. Performance of the nonlinear GAoFC is verified using a nonlinear simulation of the Space Station. We study cases of manually generated parameters rule set, GA-optimized parameters, and GA-optimized rules and parameters. Results presented substantiate the feasibility of using GA-optimized fuzzy controllers in robust nonlinear control of spacecraft

Keywords

attitude control; fuzzy control; fuzzy logic; genetic algorithms; learning systems; nonlinear control systems; robust control; space vehicles; Space Station Freedom; adaptive learning module; attitude control; fuzzy control; genetic algorithm; nonlinear control system; objective function module; optimized fuzzy logic; robust nonlinear control; spacecraft; Adaptive control; Control systems; Fuzzy control; Fuzzy logic; Genetic algorithms; Linear feedback control systems; Nonlinear control systems; Robust control; Space stations; Space vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on

Conference_Location

Orlando, FL

Print_ISBN

0-7803-1896-X

Type

conf

DOI

10.1109/FUZZY.1994.343537

Filename

343537