Delay nonlinear system predictive control on MPSO+DNN

This paper presents a novel dynamic neural network (DNN) predictive control strategy based on modified particle swarm optimization (PSO) for long time delay nonlinear process. The proposed dynamic NN structure could approximate to the actual system model and obtain the pure delay time exactly. An improved version of the original PSO is put forward to train the parameters of NN to enhance the convergence and accuracy. The effectiveness of the proposed control scheme is demonstrated by simulation as well as a test on an experiment on the actual pH Neutralization Process.