| Title |
Estimation of Optimal Control Parameters and Design of Hybrid Fuzzy Controller by Means of Genetic Algorithms |
| Authors |
이대근(Lee, Dae-Keun) ; 오성권(Oh, Sung-Kwun) ; 장성환(Jang, Sung-Whan) ; 김용수(Kim, Yong-Soo) |
| Keywords |
HFC(Hybrid Fuzzy Controller) ; GAs(Genetic Algorithms) ; weighting factor ; estimation mode(BM,CM,EM) |
| Abstract |
The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. First, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The control input for the system in the HFC combined PID controller with fuzzy controller is a convex combination of the FLC's output and PID's output by a fuzzy variable, namely, membership function of weighting coefficient. Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to automatically improve the performance of hybrid fuzzy controller. Especially, in order to auto-tune scaling factors and PID parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed to show applicability and superiority with the and of three representative processes. |