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所属单位：能源与动力学院

发表刊物：ENERGIES

关键字：second-order sliding mode observer robust estimation health parameters gas path health monitoring turbofan engine

摘要：In this paper the problem of health parameter estimation in an aero-engine is investigated by using an unknown input observer-based methodology, implemented by a second-order sliding mode observer (SOSMO). Unlike the conventional state estimator-based schemes, such as Kalman filters (KF) and slidingmode observers (SMO), the proposed scheme uses a "reconstruction signal" to estimate health parameters modeled as artificial inputs, and is not only applicable to long-time health degradation, but reacts much quicker in handling abrupt fault cases. In view of the inevitable uncertainties in engine dynamics and modeling, a weighting matrix is created to minimize such effect on estimation by using the linear matrix inequalities (LMI). A big step toward uncertainty modeling is taken compared with our previous SMO-based work, in that uncertainties are considered in a more practical form. Moreover, to avoid chattering in sliding modes, the super-twisting algorithm (STA) is employed in observer design. Various simulations are carried out, based on the comparisons between the KF-based scheme, the SMO-based scheme in our earlier research, and the proposed method. The results consistently demonstrate the capabilities and advantages of the proposed approach in health parameter estimation.

ISSN号：1996-1073

是否译文：否

发表时间：2017-07-01

合写作者：Chang, Xiaodong,鲁峰

通讯作者：黄金泉