Impulse fuzzy model based predictive control for nonlinear systems

Fuzzy and predictive control methods are two modern control strategies that have been accepted by the industry to describe and solve complex problems. The present paper introduces a fuzzy control technique, which belongs to the popular family of control algorithms, called model predictive control (MPC). This method is based on the use of a Takagi-Sugeno fuzzy model which is considered as a powerful structure for representing nonlinear dynamic systems. So, an impulse fuzzy model predictive control is used for predicting the future behavior of the output variable. A local optimization problem is formulated, which minimize the difference between the model predictions and the desired trajectory for each subsystem. Simulation results are given to illustrate the tracking performance of the proposed method.