Model predictive power control of a heat pipe cooled reactor

Abstract

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Heat pipe cooled reactor (HPR) has broad application prospects in deep space exploration, deep-sea submarine exploration, and other scenarios due to the small size, high inherent safety, and easy modularization and expansion. However, the HPR conducts thermal energy through evaporation and condensation of the working fluid inside the heat pipe. This feature makes the HPR a large time-delay system. If the power control system adopts the conventional PID algorithm, there will be a long settling time. Therefore, the model predictive control algorithm is proposed for the power control system to improve the control performance. The HPR linear model, which is developed by linearization of its nonlinear model, is chosen as the predictive model. The optimal control value is obtained by solving the optimization problem based on the predictive model and the electric power feedback value. The discrepancy between the predive model and the actual system response results in the presence of steady-state error. To solve this problem, an integral controller is added to eliminate the error. The appropriate control system parameters are tuned by the trial and error method. The proposed control system has satisfactory control performance, which can significantly shorten the settling time. The model predictive control can effectively overcome the influence of the large time-delay characteristic.

Keywords

• heat pipe cooled reactor
• model predictive control
• power control
• linearization
• online optimization