航空发动机部件性能退化参数的分布式估计算法

doi:10.7527/S1000-6893.2013.0356

Abstract

Abstract:

Aero-engine deviation parameters (EDPs) estimation is one of the key technologies of performance seeking control (PSC). The idea of using distributed filtering to estimate EDPs is proposed, because there are some disadvantages in the traditional centralized Kalman filtering,such as low computational efficiency, poor fault-tolerance, etc. A simple federated filtering with information fusion is designed to estimate the EDPs, which is based on the traditional state variable model and Kalman filtering algorithm. The advantages of the designed federated filtering are analyzed in theory in terms of the construction and recurrence equations. Finally, the capability of federated filtering is certified using a given turbo fan engine by simulation. The EDPs are estimated by applying the designed federated filtering, and the estimation results are compared with those of traditional Kalman filtering's, which show that federated filtering with distributed calculation can realize convergencde more quickly, and the estimation precision is evidently higher. This study may have some theoretical significance and practical value for the development of PSC.

Key words: aero-engine, parameter estimation, performance seeking control, Kalman filter, estimation of distribution, federated filtering

CLC Number:

V233.7

YIN Dawei, LV Riyi, CHANG Bin, YAN Xianrong. Distributed Estimation Algorithm for Aero-engine Deviation Parameters[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013, 34(12): 2716-2724.

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Distributed Estimation Algorithm for Aero-engine Deviation Parameters

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