A nonlinear model predictive tracking control strategy for modular high-temperature gas-cooled reactors

Modular high-temperature gas-cooled nuclear reactor (MHTGR) has attracted comprehensive attention for its reliable inherent safety, and an effective control strategy is needed to control the output power of the MHTGRs at the desired level. Based on model predictive control (MPC) strategy, this paper aims to develop a nonlinear power-level tracking controller for the MHTGRs. By introducing Takagi-Sugeno (TS) fuzzy system for nonlinear modeling, the nonlinear MHTGR model is represented by TS models. Based on the TS models, a nonlinear MPC (NMPC) controller is developed. Moreover, system constraints are considered, and quadratic programming (QP) is introduced for system optimization under the constraints. In addition, the system stability is analyzed based on Pole-Zero map and Nyquist diagram. To evaluate the performance of the proposed NMPC strategy, a Proportional-Integral-Derivative (PID) control strategy and a fuzzy adaptive Proportional-Integral-Derivative (FPID) control strategy are presented for comparison. The effectiveness and the advantages of the proposed NMPC strategy are demonstrated by simulation results.