Fuzzy Sampled-Data Control for DFIG-Based Wind Turbine With Stochastic Actuator Failures.

The stabilization of fault-tolerant control problem for the doubly fed induction generator (DFIG)-based wind turbine (WT) model has been investigated with stochastic actuator faults by incorporating a Takagi–Sugeno (T–S) fuzzy technique. To depict such stochastic actuator faults, the proposed model is incorporated with Markovian switching parameters for denoting various faulty modes. Besides, a novel fault-tolerant fuzzy switching control with sampled-data (SD) inputs has also been employed for eliminating the stochastic faults so that the stabilization of the system and an optimal ${\mathsf {H}}_{\infty }$ level could be ensured simultaneously. Furthermore, the stability conditions are derived by employing fuzzy Lyapunov–Krasovskii functionals (LKFs), whose matrices are membership dependent functions. Finally, the proposed control method for the stabilization problem is validated through a numerical simulation performed on the DFIG-based WT model. [ABSTRACT FROM AUTHOR]