An adaptive-cost-function optimal controller design for a PWR nuclear reactor

State Feedback Assisted Classical (SFAC) control has been developed to increase robustness of existing nuclear reactor classical controllers while improving the reactor temperature response at the same time. To attain this, a state feedback controller modifies the embedded classical controller reference signal. An optimal state feedback controller has been designed which works well near full power operating conditions. The objectives and limitations of control are different in low and high power. We use this fact to design the optimal controller and estimator with adaptive cost functions to attain the same performance at the powers other than the full power. Sensitivity of dominant closed loop poles and nonlinear simulations are used for demonstration. The results show good performance of the controller in both high and low power operation.