Adaptive PID control with neural network based predictor

In this paper, a novel approach to adaptive PID control with neural network based d-step ahead predictor is presented to deal with the control problem for a nonlinear process with time-delay. The paper is organized as follows:In section 2, both recursive and non-recursive d-step ahead predictors are presented to compensate for the influence of the time-delay on nonlinear control systems. In section 3, an adaptive PID control strategy with neural network predictor is proposed. Then, a RLS type learning algorithm is described in section 4 to speed up the learning of the feedforward neural network, thus allowing for on-line adaptive control strategies to become feasible. Finally, simulation results as well as the real-time control of a heat exchanger are illustrated.