Research on Health Parameter Estimation and Thrust Predictive Control of Aeroengine

In order to realize the safe and accurate control of aero-engine under high temperature and pressure, especially the effective control of steady state and transition state under the condition of no molting and molting, the research of aero engine health parameter estimation and direct thrust model predictive control was carried out. A nonlinear mathematical model considering aero-engine health parameters was established by using the data-driven modeling method of parameter identification and symbolic regression, and the health parameters that could not be measured directly in the model were estimated by Kalman filter (CKF) algorithm. The nonlinear model predictive control (NMPC) is designed according to the nonlinear mathematical model, control target and safety constraint of aero engine, and the objective function is optimized. The simulation results show that the Kalman filter can estimate the thrust accurately, and the adjustment time and overshoot of NMPC direct thrust controller are better than PID controller. The results show that the proposed direct thrust control system combined with CKF and NMPC and its design method can achieve rapid, accurate and safe thrust control, and provide a new idea for the design of direct thrust control system in the case of aircraft engine degradation.