基于T-S模糊模型的航空发动机模型辨识

Identification of aero-engines model based on T-S fuzzy model

关键词:  航空发动机  T-S模糊辨识模型+  反向传播法+  最小二乘法

Key words:  Aircraft engine  T-S fuzzy identification model+  Back-propagation algorithm+  Least square method

摘要:

提出了一种航空发动机的Takagi-Sugeno(T-S)模糊模型辨识方法,该方法通过最小二乘法辨识模糊模型的后件参数,通过反向传播法辨识模糊模型的前件参数,并实现了模糊模型结构的自适应优化。以航空发动机机载记录数据为依据,通过对输入输出数据的学习建立了航空发动机的T-S模糊辨识模型,通过该模型对机载记录数据的辨识,结果表明该模糊辨识模型具有辨识精度高、鲁棒性强、容错性好等特点。

Abstract:

A new identification algorithm of Takagi-Sugeno fuzzy model was proposed.In the algorithm,the conclusion parameters of each rule were identified by the least square method.The premise parameters of each rule were identified by the back-propagation method.The structure of fuzzy identification model was optimized.The T-S fuzzy identification model of an aero-engine was set up based on the real flight data recorded.Through the identification of the recorded flight data,the results show that the identification model has the advantages of high precision,good robustness and fault-tolerant ability.