Robust Fault Tolerant Control for Drive Train in Wind Turbine Systems with Stochastic Perturbations

To achieve reliable operation of wind energy conversion technology, this paper develops a robust observer based fault tolerant control technique for wind turbine drive train systems in presence of simultaneous unknown inputs, faults and Brownian perturbations. Integration of several advanced techniques, namely, augmented approach, unknown input observer method, and linear matrix inequality, is employed to estimate the means of the system states and the considered faults robustly. Based on the estimates, robust fault tolerant control strategy is implemented to drive the system trajectory convergent and eliminate the effects of faults from both actuators and sensors successfully. The control gains are selected to guarantee the convergence of the means of system states and compensate for the degradation caused by concerned faults. The observer gain is determined via a linear matrix inequality optimization such that the closed-loop system is stochastically input-to-state stable satisfying required robust performance. The designed observer based fault tolerant control can make the overall system work in a steady condition and the system outputs can be compensated to successfully track the healthy outputs in fault-free cases. Finally, the proposed fault estimation-based fault tolerant control method is applied to a drive train system of the 4.8 MW benchmark wind turbine to validate the effectiveness.