Stabilization of PMSG-based wind turbine systems with sampling information: Dynamic delay partition method

• Published in: International journal of electrical power & energy systems Vol. 149; p. 109023
• Main Authors: Kuppusamy, Subramanian, Joo, Young Hoon
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2023
• Subjects: Non-fragile sampled-data control; Stabilization; T–S fuzzy system; Uncertainty; Wind turbine systems; T–S fuzzy system; Uncertainty; Wind turbine systems; Stabilization; Non-fragile sampled-data control
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2023.109023

This paper addresses the novel stabilization criteria for a nonlinear permanent magnet synchronous generator (PMSG)-based wind turbine systems (WTS) with sampled-data information, subject to the uncertainty and controller gain variations. In this regard, the nonlinearity in PMSG-based WTS is conferred by the Takagi–Sugeno (T–S) fuzzy systems. Next, by employing the full advantages of the variable characteristic related to the sampling pattern, a novel looped-type asymmetric augmented Lyapunov-Krasovskii functional (LKF) is developed. Then, the dynamic delay partition method is the first time to be applied for the non-fragile sampled-data control design of proposed T–S fuzzy systems. Also, the less conservativeness stabilization criteria for T–S fuzzy systems are obtained in the form of linear matrix inequality. In the end, the numerical examples confirm the applicability and efficiency of the presented results. •The nonlinear PMSG-based WTS is modeled with an uncertainty of stator resistance.•The non-fragile SDC is designed for T–S fuzzy-based PMSG WTS.•By utilizing the delay partition method, the novel looped LKF is constructed.•A matrix Q in proposed LKF are all not required to be symmetric or positive definite.•The numerical examples assure the applicability and superiority of presented results.