A Model Predictive Controller for Load-Following Operation of PWR Reactors

The basic concept of a model predictive control method is to solve on-line, at each time step, an optimization problem for a finite future interval and to implement only the first optimal control input as the current control input. It is a suitable control strategy for time-varying systems, in particular, because the parameter estimator identifies a controller design model recursively at each time step, and also the model predictive controller recalculates an optimal control input at each time step by using newly measured signals. The proposed controller is applied to the integrated power level and axial power distribution controls for a Korea Standard Nuclear Power Plant (KSNP). The power level and the axial shape index are controlled by two kinds of the five regulating control rod banks and the two part-strength control rod banks together with the automatic adjustment of boric acid concentration. The three-dimensional reactor analysis code, Multipurpose Analyzer for Static and Transient Effects of Reactor, which models the KSNP, is interfaced to the proposed controller to verify the proposed controller for controlling the reactor power level and the axial shape index. It is known from numerical simulations that the proposed controller exhibits very fast tracking responses.