Fuzzy generalized predictive control baked on T-S fuzzy model

A kind of T-S fuzzy model is established for nonlinear system by a fast fuzzy identification method based on fuzzy logic rules. The consequent parameters are identified by Kalman filter algorithm. According to the dynamic linearization model of the T-S fuzzy model, a generalized predictive control strategy is adopted. Comparing with the previous fuzzy generalized predictive control arithmetic, the proposed method is simple, model identification is high-precision and the compute quantity is reduced greatly. The simulation results show that this method is effective.