Paper Info
Title
Optimal and stable fuzzy controllers for nonlinear systems subject to parameter uncertainties using genetic algorithm
Abstract
This paper tackles the control problem of nonlinear systems subject to parameter uncertainties based on the fuzzy logic approach and genetic algorithm (GA). In order to achieve a stable controller, the TSK fuzzy plant model is employed to describe the dynamics of an uncertain nonlinear plant. A fuzzy controller and the corresponding stability conditions are derived. The parameters of the fuzzy controller and the solution to the stability conditions are determined using GA. In order to obtain the optimal performance, the membership functions of the fuzzy controller are obtained automatically by minimizing a defined fitness function using GA.
Year
DOI
Venue
2001
10.1109/FUZZ.2001.1009103
Fuzzy Systems, 2001. The 10th IEEE International Conference  
Keywords
Field
DocType
fuzzy control,genetic algorithms,nonlinear systems,optimal control,stability,uncertain systems,TSK model,fitness function,fuzzy control,fuzzy logic,genetic algorithm,membership functions,nonlinear systems,optimal control,parameter uncertainty,stability,uncertain systems
Control theory,Mathematical optimization,Defuzzification,Control theory,Computer science,Fuzzy logic,Fuzzy set,Fitness function,Adaptive neuro fuzzy inference system,Fuzzy control system,Fuzzy number
Conference
Volume
Citations 
PageRank 
2
4
0.67
References 
Authors
4
4
Name
Order
Citations
PageRank
H. K. Lam13618193.15
S. H. Ling260940.29
F. H. Frank Leung392.57
Peter Kwong-Shun Tam415724.65