Development of a Robust Model-Based Reactivity Control System

Abstract

Present digital control system hardware allows the implementation of advanced computerized control algorithms with a high degree of sophistication. In addition to improving disturbance rejection and demand following capabilities, computerized algorithms can provide robustness for abnormal operating conditions while providing diagnostic information on either the plant or the controller itself. This paper describes the development and implementation of a digital model-based reactivity control system that incorporates a knowledge of the plant physics into the control algorithm to improve system performance. This controller is composed of a model-based module and a modified proportional-integral-derivative (PIO) module. The model-based module has an estimation component to synthesize unmeasurable process variables that are necessary for the control action computation. These estimated variables, besides being used within the control algorithm, will be used for diagnostic purposes by a supervisory control system under development. The PID module compensates for inaccuracies in model coefficients by supplementing the model based module output with a correction term that eliminates any demand tracking or steady state errors. This control algorithm has been applied to develop controllers for a simulation of liquid metal reactors in a multimodular plant. It has shown its capability to track demands in neutron power much more accurately than conventional controllers, reducing overshoots to almost negligible values while providing a good degree of robustness to unmodeled dynamics.