Estimation and Optimal Feedback Control Theory Applied to a Nuclear Boiling Water Reactor

A linear dynamic model, a quadratic performance index, and a Gaussian stochastic noise assumption (LQG-theory) have been used to design a feedback controller for a simulated current design 1100-MW(e) boiling water reactor. The total plant power control is studied in the range of 65 to 100% of rated power, with main emphasis on load-following control. An extended Kalman filter used in parallel with the compensator during normal operation is suggested for on-line parameter estimation. The algorithms are considered suitable for implementation in direct digital control.