Integration of MPC and SOLADRC to Optimize PWR Performance

Abstract

Controlling pressurized water reactors (PWRs) is a challenging task due to their inherent nonlinearity, modeling uncertainties, time-varying parameters, and multi-input multi-output (MIMO) nature. These factors require advanced control strategies to maintain safe and efficient operations. This paper focuses on the nonlinear controller design for PWRs, where external disturbances and system uncertainties are the primary challenges. To enhance the control performance of PWRs, the authors propose an integrated approach using Model Predictive Control (MPC) and Second Order Linear Active Disturbance Rejection Control (SOLADRC). MPC is utilized to optimize the reactor core by predicting the dynamic behavior of the system and proactively adjusting the control inputs. SOLADRC is employed to provide robust regulation of key operating parameters, such as reactor power, coolant temperature, and pressure, in the presence of both known and unknown disturbances. Comprehensive simulations and analysis demonstrate the effectiveness of the integrated MPC-SOLADRC approach in improving the PWR's operational efficiency, flexibility, and safety margins. The results show that the combined MPC and SOLADRC strategy outperforms traditional control methods in terms of set point tracking, disturbance rejection, and constraint handling. This work contributes to the advancement of control optimization techniques for MIMO systems, paving the way for enhanced safety, reliability, and economic performance of PWR.