Fault detection of a benchmark wind turbine using interval analysis

Mojtaba Tabatabaeipour, Peter Fogh Odgaard, T. Bak

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


This paper investigates a state estimation set-membership approach for fault detection of a benchmark wind turbine. The main challenges in the benchmark are high noise on the wind speed measurement and the nonlinearities in the aerodynamic torque such that the overall model of the turbine is nonlinear. We use an effective wind speed estimator to estimate the effective wind speed and then using interval analysis and monotonicity of the aerodynamic torque with respect to the effective wind speed, we can apply the method to the nonlinear system. The fault detection algorithm checks the consistency of the measurement with a closed set that is computed based on the past measurements and a model of the system. If the measurement is not consistent with this set, a fault is detected. The result demonstrates effectiveness of the method for fault detection of the benchmark wind turbine.
Original languageEnglish
Title of host publicationProceedings of the American Control Conference 2012
Publication date2012
ISBN (Print)978-1-4577-1096-4
Publication statusPublished - 2012
Externally publishedYes
EventAmerican Control Conference (ACC 2012) - Fairmont Queen Elizabeth, Montréal, Canada
Duration: 27 Jun 201229 Jun 2012


ConferenceAmerican Control Conference (ACC 2012)
LocationFairmont Queen Elizabeth
Internet address


  • aerodynamics
  • control nonlinearities
  • fault diagnosis
  • nonlinear control systems
  • torque control
  • wind turbines


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