LAPSE:2019.0109
Published Article
LAPSE:2019.0109
Gas-Path Health Estimation for an Aircraft Engine Based on a Sliding Mode Observer
Xiaodong Chang, Jinquan Huang, Feng Lu, Haobo Sun
January 7, 2019
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.
Keywords
aircraft engines, health estimation, linear matrix inequalities (LMIs), modeling uncertainties, sliding mode observer (SMO)
Suggested Citation
Chang X, Huang J, Lu F, Sun H. Gas-Path Health Estimation for an Aircraft Engine Based on a Sliding Mode Observer. (2019). LAPSE:2019.0109
Author Affiliations
Chang X: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Road, Nanjing 210016, China [ORCID]
Huang J: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Road, Nanjing 210016, China
Lu F: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Road, Nanjing 210016, China
Sun H: College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Road, Nanjing 210016, China
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Journal Name
Energies
Volume
9
Issue
8
Article Number
E598
Year
2016
Publication Date
2016-07-29
Published Version
ISSN
1996-1073
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PII: en9080598, Publication Type: Journal Article
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LAPSE:2019.0109
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doi:10.3390/en9080598
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Jan 7, 2019
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Calvin Tsay
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