Fuzzy identification and control algorithms based on an ETSK model

Abstract This paper presents an extended Takagi-Sugeno-Kang Model (ETSK) based on extension principle. Its analytic expression is derived and an algorithm to identify such a model is proposed. A Variable Weights TSK Model (VWTSK) which is equivalent to ETSK model is induced, and an ETSK-model-based fuzzy control algorithm is presented. In this algorithm the fuzzy control rules are designed according to the rules of the VWTSK model. Simulation shows that an ETSK model can give out more accurate long-range predictions and the control algorithm can achieve better control performance than fuzzy PID control method.