Fuzzy modeling of thermal process based on chaos genetic algorithm

In view of modeling problems of complicated nonlinear systems, a generalized T-S fuzzy modeling approach based on chaos genetic algorithm is presented. In this method, adaptive generalized Gaussian membership function is used, and its figure is optimized by chaos immigrant genetic algorithm, which can overcome shortcomings the traditional fuzzy cluster algorithm has, such as a large quantity of calculation, prone to dead center, local minimum and center redundancy in the iterative optimization of cluster center, and it shows great performance in antecedent parameters estimation. Finally, effectiveness and practicability of this method is demonstrated by the simulation results of the Box-Jenkins model and the overheated steam system.