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

Abstract

SummaryThis 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 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 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.

Optimal captured power control of variable speed wind turbine systems: Adaptive dynamic programming approach

“…Among RE sources, wind energy is known as a widely available resource. [1][2][3] In order to generate electricity, a wind turbine is connected to an electrical generator and a power electronic system. Based on the working features, the wind energy generation system is classified into fixed-speed and variable-speed wind turbines.…”