Takagi-Sugeno sliding mode observer design for load estimation and sensor fault detection in wind turbines

The performance and reliability of pitch control systems significantly influences the functional safety of wind turbines. In this paper, an observer-based fault detection approach for a class of nonlinear systems, which can be modeled as Takagi-Sugeno (TS) fuzzy models, is presented and applied to electro mechanical pitch drive systems of wind turbines. To achieve robustness we propose a TS fuzzy observer combined with sliding mode that deals with unmeasurable premise variables and bounded uncertainties in the plant. It is shown that this formulation allows sensor fault estimation and load reconstruction based on an equivalent output error injection approach. The stability of the error dynamics is ensured by sufficient linear matrix inequality (LMI) conditions. Based on a derived physical model of the pitch drive system and the unknown but bounded wind loads the robust observer is systematically designed using the TS system form of the plant. Simulation results demonstrate the effectiveness of the proposed scheme.