Adaptive neural predictive control for nonlinear systems with time-delay

This work presents a neural predictive control for a class of single-input single-output nonlinear systems with known time-delay. A neural predictive control law is developed based on the minimization of a generalized predictive performance criterion. A real-time adaptive control algorithm, including a neural predictor and a neural predictive controller, is proposed, and the local stability of the closed-loop control system is investigated as well. Simulation results reveals that the proposed control gives satisfactory tracking and disturbance rejection performance for two illustrative time-delay nonlinear systems. Experimental results for a variable-frequency oil-cooling control process are performed which have shown effectiveness of the proposed method under the conditions of setpoint and load changes.