A novel affine qLPV model derivation method for fault diagnosis H&lt;inf&gt;&amp;#x221E;&lt;/inf&gt; performance improvement

Salar, Amin; Meskin, Nader; Khorasani, K.

doi:10.1109/acc.2015.7170836

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2017

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“…Many techniques have been developed for fault diagnosis of LPV systems in the literature such as the geometric approach, the inversion based methods, the eigenstructure assignment, robust approaches like the norm‐based optimization filters, interval observers, unknown input observers, and sliding mode observers . Despite the benefits of LPV‐based FDI filter design approaches, the LPV model used as the basis of the LPV observer design might not perfectly represent the original nonlinear behavior of the system, which may eventually lead to false alarms or missing detections.…”

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confidence: 99%

Adaptive sliding mode–based diagnosis of actuator faults for LPV systems

Rahme

Meskin

Mohammadpour

2017

Adaptive Control & Signal

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In this paper, an adaptive sliding mode observer is developed for actuator fault diagnosis of linear parameter-varying systems. The main advantage of the proposed approach is its ability to cope with time-varying distribution matrix in linear parameter-varying systems. Furthermore, the proposed adaptive observer is characterized by its output robustness against parameter uncertainties and disturbances without any a priori knowledge about their bounds. The efficiency of the proposed fault diagnosis approach is validated using simulation studies.

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