Sensor fault tolerant control of a wind turbine via Takagi-Sugeno fuzzy observer and model predictive control

This paper proposes an approach to fault tolerant control (FTC) of a wind turbine subject to sensor faults. Both analytical and hardware redundancies are utilized in this approach. A residual generator based on a Takagi-Sugeno (T-S) fuzzy observer is proposed as the fault detection and isolation (FDI) unit. A T-S fuzzy observer design method via online eigenvalue assignment is proposed. It is shown that single residual can be utilized to identify different sensor faults by analyzing the characteristics of the residual. Model predictive control (MPC) based on T-S fuzzy modeling is proposed as the wind turbine controller to take into account the turbine system nonlinearity and physical constraints of the turbine actuators.