Abstract:

It is a new way apply intelligent algorithms to the identification of T-S fuzzy systems. This paper gives a detail description of several intelligent optimization algorithms and their application of fuzzy identification, such as genetic algorithm (GA), particle swarm optimization (PSO) algorithm and bacterial foraging optimization (BFO) algorithm. The parameters optimization processes of these algorithms on the T-S fuzzy model are also provided. Finally, the described methods are applied to the modeling of a nonlinear dynamic system, and the simulation results are analyzed in detail. This paper provides an opportunity for a further understanding of the effects of these methods on the process of parameters optimization in fuzzy modeling.