关键词: 航空发动机, 自适应模型, 参数估计, 卡尔曼滤波, 渐消因子

Abstract: The deviation of the aero-engine on-board adaptive system model could not be completely eliminated, which may result in serious estimation deviation and filtering divergence. A new Kalman estimation algorithm with fading factor was proposed. Adjusting the weight of innovation covariance and increasing the effect on realistic measurement data in state estimation, the accuracy of aero-engine parameters estimation was ensured. Compared with the conventional Kalman filtering, the simulation results shows that the method proposed can restrain filtering divergence and obtain the high accuracy of estimation and the short convergence time. The derivation of the new method is simple, the computation amount is little, and the engineering application value is high.

Key words: aero- engine, adaptive model, parameter estimation, Kalman filter, fading factor