Emotional learning based intelligent controller for a PWR nuclear reactor core during load following operation

The design and evaluation of a novel approach to reactor core power control based on emotional learning is described. The controller includes a neuro-fuzzy system with power error and its derivative as inputs. A fuzzy critic evaluates the present situation, and provides the emotional signal (stress). The controller modifies its characteristics so that the critic’s stress is reduced. Simulation results show that the controller has good convergence and performance robustness characteristics over a wide range of operational parameters.