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Finite time estimation of actuator faults, states, and aerodynamic load of a realistic wind turbine

Author

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  • Rahnavard, Mostafa
  • Ayati, Moosa
  • Hairi Yazdi, Mohammad Reza
  • Mousavi, Mohammad

Abstract

This paper provides finite time estimation of wind turbine actuator faults and unknown aerodynamic load. Furthermore, finite-time state estimation of drivetrain, generator, and pitch subsystems are addressed in the contrary of asymptotic state/fault estimation in previous works. A realistic wind turbine model, incorporating the aero-elastic FAST simulator, is considered as the simulation example. Generally, aerodynamic load is not measurable in real applications due to instrument limitations, then, it is considered as an unknown input in this study. A novel terminal sliding mode observer is introduced for finite-time estimation of generator/convertor states, faults, and unknown aerodynamic load. Pitch actuator hydraulic pressure drop is modelled as an additive fault, by introducing a fault indicator. Then, two cascaded sliding mode observers are exploited for each pitch subsystem, to provide finite time state and fault reconstructions. Sufficient number of design parameters helps to achieve desired accuracy and convergence time. Finally, simulation results authenticate finite time estimation of wind turbine states and simultaneous actuator faults.

Suggested Citation

  • Rahnavard, Mostafa & Ayati, Moosa & Hairi Yazdi, Mohammad Reza & Mousavi, Mohammad, 2019. "Finite time estimation of actuator faults, states, and aerodynamic load of a realistic wind turbine," Renewable Energy, Elsevier, vol. 130(C), pages 256-267.
    • Handle: RePEc:eee:renene:v:130:y:2019:i:c:p:256-267
    DOI: 10.1016/j.renene.2018.06.053
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    References listed on IDEAS

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    1. Pierre Tchakoua & René Wamkeue & Mohand Ouhrouche & Fouad Slaoui-Hasnaoui & Tommy Andy Tameghe & Gabriel Ekemb, 2014. "Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges," Energies, MDPI, vol. 7(4), pages 1-36, April.
    2. Shi, Fengming & Patton, Ron, 2015. "An active fault tolerant control approach to an offshore wind turbine model," Renewable Energy, Elsevier, vol. 75(C), pages 788-798.
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    Cited by:

    1. Xin Wang & Seyed Mehdi Abtahi & Mahmood Chahari & Tianyu Zhao, 2022. "An Adaptive Neuro-Fuzzy Model for Attitude Estimation and Control of a 3 DOF System," Mathematics, MDPI, vol. 10(6), pages 1-16, March.

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