Fuzzy Event-Triggered Control for Grid-Connected PMSM Model With Stochastic Disturbances

This article aims to model and investigate the dynamical properties of a grid-connected permanent magnet synchronous motor (PMSM) in wind energy conversion systems (WECSs). Considering the dc-link capacitor in voltage equations of PMSM can cause hyperchaotic solution behavior, whereas the conventional PMSM model exhibits chaotic solutions. In addition, disturbances are inevitable in WECS hence in this study the aerodynamics of PMSM is considered as stochastic disturbances that can degrade the performance of the WECSs. As a result, grid-connected PMSM is modeled as stochastic differential equations with nonlinear characteristics. Due to nonlinearity, investigating the stability properties of PMSM with dc-link is economically expensive. In this regard, an equivalent Takagi–Sugeno (T–S) fuzzy model can be derived to mimic the dynamical characteristics of the stochastic PMSM model with the help of fuzzy membership grades. Overall this study focuses on designing a suitable control algorithm that guarantees the global stable performance of T–S-based linear hyperchaotic PMSM model involving stochastic disturbances. Among various controllers, an event-triggered-based sampled-data control scheme with continuous-type network transmission delay is considered to be effective for the proposed model with disturbances. Theoretically, the Lyapunov stability theory is employed to derive sufficient stability conditions in terms of solvable linear matrix inequalities. Technically, the numerical simulations are performed with the experimental range of parameter values to validate the effectiveness of the proposed theoretical frameworks.