GENERALIZED TAKAGI-SUGENO FUZZY LOGICAL SYSTEM OPTIMAL PARAMETER IDENTIFICATION BASED ON GENETIC ALGORITHM
Li He · 2002
In Takagi-Sugeno fuzzy logical system, its membership functions have no self-adaptability and the number of fuzzy ruels is defined subjectively. In this paper, a generalized Takagi-Sugeno fuzzy logical system model is quoted. In search of optimal parameters of the generalized Takagi-Sugeno model the matrix coding is adopted. The structure of the generalized Takagi-Sugeno model is evolved by GA and the resulting suboptimal solution can be found quickly, which has lower complexity and approximates to a nonliner system very well. The validity of this method has been demonstrated by a numerical simulation.