Fault Tolerant Control of a Nuclear Steam Generator in the presence of Sensor Biases

Abstract

Steam Generator (SG) is one of the crucial components in a nuclear power plant where nuclear reactors like pressurized water reactors (PWR) and pressurized heavy water reactors (PHWR) are used. For safe operation of SG in power plants, the control of water level becomes very crucial. Poor control of the water level in SG can lead to frequent reactor shutdowns. The occurrence of biases in the measurement of level and pressure sensors used in the SG control system can result in significant degradation of the closed-loop performance. This work aims to introduce a fault tolerant control framework to arrest the performance degradation of conventional controllers in the presence of sensor bias. Initially, the bias present in the measurements is modeled as a time varying parameter and estimated using a suitably modified version of RNK based state and parameter estimator approach. Using the sensor bias estimates, the measurements are corrected and further used in the controller. The effectiveness of the proposed framework of FTC in the presence of sensor bias is demonstrated by carrying out simulation studies on a benchmark SG system. Analysis of simulation results reveals that the proposed FTC framework gives similar results to that of fault free case.