Extended Kalman Filter Infusion Algorithm Design and Application Characteristics Analysis to Stochastic Closed Loop Fan Speed Control of the Nonlinear Turbo-Fan Engine

摘要

An Extended Kalman Filter (EKF) was proposed for fan speed signal infusion of the turbo fan engine. Firstly, a nonlinear discrete time analytical engine model was identified using a general nonlinear engine mathematical model based on least square method. Afterwards, fan speed signal infusion EKF algorithm was designed based on optimal filtering theory for nonlinear multistage dynamic process. Then, Kalman gains of EKF algorithm were offline tuned, and fan speed signal was synthesized by using 6 different combinations of 4 sensed parameters. T_(25), T_3, P_(s3) and EGT as input of the infusion EKF algorithm, and the infused fan speed signal under different infusion combinations were compared with the actual fan speed signal sensed directly from nonlinear engine model using small step test cases. After that, fan speed closed loop control simulations were conducted using the infused fan speed signal as feedback, and algorithms with 6 different infusion combinations were analyzed with respects to control performance and stability using small step command test case under ideal environment. Finally, closed loop control simulation was conducted with the fan speed EKF infusion signal from selected 3 parameter infusion algorithm as feedback using both small and big step command test case under stochastic environment. The results show that, under both ideal (without consideration of noise) and stochastic conditions, the proposed EKF fan speed signal infusion algorithm has a good closed loop control performance