| Title |
Optimal Design for Rule-Based Fuzzy Logic Controller Using GA |
| Authors |
노기갑(No, Gi-Gap) ; 주영훈(Ju, Yeong-Hun) ; 박진배(Park, Jin-Bae) |
| Keywords |
Fuzzy Logic Controller ; Genetic Algorithm ; Parameter Optimization |
| Abstract |
This paper presents an optimal design method for fuzzy logic controllers using genetic algorithms. In general, the design of fuzzy logic controllers has difficulties in the acquisition of exper's knowledge and relies to a great extent on empirical and heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored, and parameters of the fuzzy logic controller obtained by expert's control action may not be global. To solve these problems, the proposed method using genetic algorithms in this paper, can tune the parameters of fuzzy logic controller including scaling factors and determine the appropriate number of fuzzy reles systematically and automatically. We provide the second drder dead time plant and inverted pendulum system to evaluate the feasibility and generality of our proposed method. Comparison shows that the proposed controller can producd higher accuracy and a smaller number of fuzzy rules than manually tuned fuzzy logic controller. |