Gain scheduling model predictive control for a space thermionic nuclear reactor

Space thermionic nuclear reactor (STNR) has the characteristics of large delay and strong nonlinearity. It is difficult to obtain the satisfied performance with traditional control system. Model prediction control (MPC) is adopted in this study. The control law is designed and optimized through the prediction model and objective performance function. The problem of poor control performance of large delay system is solved and fast regulation is achieved. The model predictive controllers are designed at different power levels. Gain scheduling method is utilized to improve the tracking accuracy of the nonlinear system. This approach enables stable operation of STNRs across the full-power range. It is shown from the simulation analysis under the representative operational scenarios that the model predictive control system based on gain scheduling has smaller overshoot and settling time than the traditional control system. The fluctuations of major parameters are reduced significantly. Therefore, the proposed gain scheduling model predictive control provides a promising strategy to the control of STNR.