Intelligent control for a nuclear power plant using artificial neural networks

In this paper, an approach based on neural networks for the control system design of a pressurized water reactor (PWR) is presented. A reference model which incorporates a static projective suboptimal control law under various operating conditions is used to generate the necessary data for training the neurocontroller. The designed approach is able to control the nuclear reactor in a robust manner. Simulation results presented reveal that it is feasible to use artificial neural networks to improve the operating characteristics of the nuclear power plants.<>