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    A neuro-adaptive maximum power tracking control of variable speed wind turbines with actuator faults

    Access Status
    Fulltext not available
    Authors
    Habibi, H.
    Nohooji, H.
    Howard, Ian
    Date
    2018
    Type
    Conference Paper
    
    Metadata
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    Citation
    Habibi, H. and Nohooji, H. and Howard, I. 2018. A neuro-adaptive maximum power tracking control of variable speed wind turbines with actuator faults, pp. 63-68.
    Source Title
    2017 Australian and New Zealand Control Conference, ANZCC 2017
    DOI
    10.1109/ANZCC.2017.8298486
    ISBN
    9781538621783
    School
    School of Civil and Mechanical Engineering (CME)
    URI
    http://hdl.handle.net/20.500.11937/68341
    Collection
    • Curtin Research Publications
    Abstract

    © 2017 IEEE. This paper presents a neural adaptive fault tolerant control design of wind turbines in partial load operation. The controller is designed to be robust against actuator faults as well as noise, while keeping the wind turbine generating as much power as possible. The wind speed variation is considered as an external disturbance, and an adaptive radial basis function neural network is utilized to estimate aerodynamic torque. Estimation of a fault size and establishment of a desired trajectory are adopted in the design. Using the proposed method, the reliability of wind power generation is increased so as to track the optimum power point under faulty conditions, close to the fault free case. Uniformly ultimately boundedness of the closed-loop system is achieved using Lyapunov synthesis. The designed controller is verified via numerical simulations, showing comparison with an industrial reference controller, using predefined criteria.

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