Stabilization of permanent magnet synchronous generator-based wind turbine system via fuzzy-based sampled-data control approach

Abstract

This study concerns the stabilization analysis for nonlinear permanent magnet synchronous generator (PMSG)-based wind turbine system under fuzzy-based memory sampled-data (FBMSD) control scheme. In this regard, the Takagi-Sugeno (T-S) fuzzy theory is utilized in the conversion of the proposed nonlinear model into linear-sub models and the corresponding FBMSD controller is designed. The paper introduces a suitable Lyapunov–Krasovskii functional that contains the information about the length of the sampling interval and a constant transmission delay. In order to stabilize the proposed system, sufficient conditions are derived in the form of linear matrix inequalities. As a test benchmark, the derived T-S fuzzy PMSG model is evaluated with a particular data set values and then validated with derived conditions. Besides that, the dynamical nature of system variables with respect to a blade pitch angle of the wind turbine system also discusses along with d-q axes inductance via numerical simulations. Finally, a comparison of derived conditions with the existing works is discussed to prove the less conservatism of the proposed method.