Abstract: A new constrained state feedback model predictive control approach of nonlinear system based on T-S fuzzy model is developed by combining T-S fuzzy model with constrained state feedback model predictive control based on particle-swarm optimization(PSO).It is used to solve the control problems of process such as CSTR reactor with highly nonlinear and constrains.A constrained state feedback model predictive controller is devised for each subsystem of T-S fuzzy model.In terms of parallel distributed compensation(PDC)fuzzy control theory，control movement and membership function of each subsystem can be calculated and used synthetically to calculate the fuzzy control movement of the whole control system.The control system of a continuous stirred tank reactor is simulated with different initial states，setpoint values and predict steps.The simulation results show that the proposed approach is effective and feasible.

Key words: predictive control, nonlinear, T-S fuzzy model, particle swarm optimization, CSTR

关键词: 预测控制, 非线性, T-S模糊模型, 粒子群优化算法, 连续搅拌反应釜