Nonlinear observer-based fault detection and isolation for wind turbines

Reza Katebi, Abdulhamed Moh Suliman Hwas

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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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.
Original languageEnglish
Title of host publicationIEEE 22nd Mediterranean Conference on Control and Automation
Place of PublicationPiscataway, New Jersey
Publication statusAccepted/In press - Jun 2014


  • fault diagnosis
  • nonlinear systems
  • renewable energy and sustainability
  • state dependent differential riccati equation


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