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Energies 2016, 9(8), 598; doi:10.3390/en9080598

Gas-Path Health Estimation for an Aircraft Engine Based on a Sliding Mode Observer

College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Road, Nanjing 210016, China
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Academic Editor: Chang Sik Lee
Received: 7 June 2016 / Revised: 21 July 2016 / Accepted: 21 July 2016 / Published: 29 July 2016
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Abstract

Aircraft engine gas-path health monitoring (GPHM) plays a critical role in engine health management (EHM). Among model-based approaches, the Kalman filter (KF) has been widely employed in GPHM. The main shortcoming of KF-based scheme lies in the lack of robustness against uncertainties. To enhance robustness, this paper describes a new GPHM architecture using a sliding mode observer (SMO). The convergence of the error system in uncertainty-existing circumstances is demonstrated, and the proposed method is developed to estimate components’ performance degradations regardless of modeling uncertainties. Simulations using a nonlinear model of a turbofan engine are presented, in which health monitoring problems are handled by the KF and the SMO, respectively. Results indicate the proposed approach possesses better diagnostic performance compared to the KF-based scheme, and the SMO shows its strong robustness and great potential to be applied to GPHM. View Full-Text
Keywords: aircraft engines; health estimation; modeling uncertainties; sliding mode observer (SMO); linear matrix inequalities (LMIs) aircraft engines; health estimation; modeling uncertainties; sliding mode observer (SMO); linear matrix inequalities (LMIs)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chang, X.; Huang, J.; Lu, F.; Sun, H. Gas-Path Health Estimation for an Aircraft Engine Based on a Sliding Mode Observer. Energies 2016, 9, 598.

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