Non-fragile event-triggered control for PMSM model with stochastic disturbances

This paper aims to design a non-fragile event-triggered control algorithm to stabilize the performance of wind energy conversion systems involving permanent magnet synchronous motor in terms of differential model. In general, the dynamical characteristics of wind energy conversion systems can be explored in terms of an ordinary differential model comprised of voltage equations, mechanical, and electrical energy factors. Based on the literature, a three-dimensional model is commonly used to investigate qualitative behaviors, such as stability, bifurcation, and chaos solutions. However, the models proposed in the literature are deterministic in nature, and if aerodynamics is involved in the rotational speed, then it becomes necessary to formulate the stochastic model. Therefore, the present paper modeled a nonlinear permanent magnet synchronous motor with stochastic disturbances in which the randomness is modeled as a derivative of white noise say Brownian motion. Further, this paper introduces Takagi-Sugeno-based sub-models which are linear in nature but holds the dynamical properties of proposed nonlinear model. Furthermore, this study presents a theoretical framework that establishes stable conditions for the stabilization of permanent magnet synchronous motors through linear matrix inequalities. Lyapunov stability theory and Ito's calculus theory are utilized to guarantee the global asymptotic stability of Takagi-Sugeno fuzzy-based permanent magnet synchronous motor involving random disturbances.