Takagi-Sugeno fuzzy modelling and robust fault reconstruction for wind turbine systems

In this study, a robust fault reconstruction approach is proposed for the 4.8 MW wind turbine benchmark system. Firstly, through weighted combination of a number of locally valid linear systems, the nonlinear wind turbine model is well represented by a Takagi-Sugeno fuzzy model. Then, augmented system approach jointly with unknown input fuzzy observer technique are utilized to estimate faults and system states simultaneously, while decouple a part of unknown inputs which consist both system perturbations and Takagi-Sugeno modelling errors. After that, linear matrix inequality approach is used to ensure convergence of estimation error and attenuate the influences from un-decoupled unknown inputs. Finally, the proposed algorithms are demonstrated to be effective by using the 4.8 MW wind turbine benchmark system.