Nonlinear observer-based fault detection and isolation for wind turbines

Katebi, Reza and Hwas, Abdulhamed Moh Suliman; (2014) Nonlinear observer-based fault detection and isolation for wind turbines. In: IEEE 22nd Mediterranean Conference on Control and Automation. IEEE, Piscataway, New Jersey. (In Press)

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Abstract

This paper is concerned with the development of a novel nonlinear observer-based scheme for early Fault Detection and Isolation (FDI) in wind turbines. The method is based on designing a nonlinear observer using State Dependent Differential Riccati Equation (SDDRE) and a nonlinear model of the 5MW wind turbine. The fault detection system is designed and optimized to be most sensitive to system faults and least sensitive to system disturbances and noises. The comparison of system outputs with nonlinear observer outputs are given to demonstrate good estimation performance. The residual generator based on the nonlinear observer is also employed to develop a monitoring system. Simulation results presented to illustrate that the proposed method is robust and can detect and isolate a fault or multi-faults in sensors of the wind turbine.

ORCID iDs

Katebi, Reza ORCID logoORCID: https://orcid.org/0000-0003-2729-0688 and Hwas, Abdulhamed Moh Suliman;
CORE (COnnecting REpositories)