Abstract:

For dynamic systems with complex, ill conditioned, or nonlinear characteristics, the fuzzy model based on fuzzy sets is very useful to describe the properties of dynamic systems using fuzzy inference rules. Nonlinear system modeling using fuzzy method is discussed in this paper. First, the fuzzy space of input variables is partitioned by means of on line fuzzy competitive learning. Further, the parameters of the fuzzy model are identified by means of Kalman filtering algorithm. The simulation results demonstrate that the proposed method is practical and efficient.

Key words: fuzzy competitive lear ning, on- line identifica tion, Ka lman filter ing a lgor ithm, nonlinear systems