Title :
Genetic algorithm based fuzzy controller for nonlinear systems
Author :
Jamshidifar, Ali A. ; Lucas, Caro
Author_Institution :
Amirkabir Univ. of Technol., Tehran, Iran
Abstract :
A genetic algorithm (GA) based fuzzy approach for on-line process control is proposed in this paper. In this approach, a TSK fuzzy controller is used to control the system. To reduce the fuzzy system design effort and to find the optimum fuzzy controller parameters, GA has been employed. It is also possible to emphasize on the system response specification by changing the fitness function and then finding the best controller parameters. The simulation results indicate that the proposed approach works well.
Keywords :
controllers; fuzzy control; genetic algorithms; nonlinear systems; TSK fuzzy controller; controller parameters; fitness function; fuzzy system design; genetic algorithm; nonlinear systems; on-line process control; system response specification; Control systems; Control theory; Fuzzy control; Fuzzy systems; Genetic algorithms; Intelligent control; Mathematical model; Nonlinear control systems; Nonlinear systems; Process control;
Conference_Titel :
Intelligent Systems, 2004. Proceedings. 2004 2nd International IEEE Conference
Print_ISBN :
0-7803-8278-1
DOI :
10.1109/IS.2004.1344849
