Fuzzy sampled-data control of PMSG-based wind turbine systems with random occurring uncertainties

This article investigates the robust stability of permanent magnet synchronous generator (PMSG)-based wind turbine (WT) systems with randomly occurring uncertainties (ROUs) under a fuzzy sampled-data control scheme. To accomplish this, the norm-bounded uncertainties in the d - q inductance, system inertia, and stator resistance are considered, which are modeled as ROUs by using certain Bernoulli distributed white noise sequences. The nonlinear PMSG-based WT systems can be expressed as local linear systems with a Takagi-Sugeno (T-S) fuzzy approach. To achieve stability performance against such kinds of uncertainties and external disturbances, fuzzy-based sampled-data control is designed for the proposed model. Then, the sufficient conditions are derived and expressed in the form of linear matrix inequalities based on looped-Lyapunov functionals, which ensure the asymptotic stability of the closed-loop T-S fuzzy model for the nonlinear PMSG-based WTs with an H-8 performance index. Finally, the derived conditions are validated with the proposed model and confirm the effectiveness of the proposed control scheme against the uncertainties and disturbances. Moreover, a comparison example is conducted to show the less conservative nature of the derived conditions.