Iterative predictive control method for batch system based on recurrent fuzzy neural networks model

Aim at model identification and predictive control problems existing in nonlinear industrial processes, this paper proposes a linear fuzzy neural network model which approach to original formula of the nonlinear system in the time index, then on this basis, a novel iterative predictive control algorithm is put forward to achieve effectively tracking performance in spite of model errors and disturbance. The simulation results show the effectiveness and feasibility of the algorithm.