Event-Based $H_{\infty}$ Fault Detection for Buck Converter With Multiplicative Noises Over Network

Abstract

This paper deals with the $H_{\infty }$ fault detection (FD) problem for a class of buck converter with the transmission-induced multiplicative noises and the event-triggered scheme under the network environment. The model of buck converter is approximated by a nonlinear model, and it is further analyzed based on the electricity knowledge. Due to the dynamic characteristics of network transmission, multiplicative noises need to be considered, which are described as a product of some uncorrelated standardized normal distribution and the transmitted signal. Meanwhile, an event-triggered mechanism is utilized for the purpose of reducing the energy consumption, and an FD observer is designed to detect the fault presented in buck converter. Some novel sufficient conditions are given in terms of linear matrix inequalities to guarantee the robust stability of the FD system, and the $H_{\infty }$ optimal fault tracking performance index is also achieved. Finally, an illustrative example is provided to show the validity and merit of the proposed method.