The paper presents a model-reference neural predictive controller design for a class of single-input single-output nonlinear systems with known time-delay. The control law is developed based on the minimization of a cost function with the model reference scheme and
the neural-network-based predictive performance criterion. A real-time adaptive control algorithm, including a neural predictor and a model-reference neural predictive controller, is proposed. Simulation results reveal that the proposed controller gives satisfactory tracking and disturbance rejection performance for some illustrative discrete-time nonlinear time-delay systems.
