Fault detection of nonlinear stochastic systems via a dynamic event-triggered strategy

Abstract

This paper studies the fault detection problem of nonlinear stochastic systems with randomly occurring nonlinearity and missing measurements via a dynamic event-triggered strategy. Firstly, the dynamic event-based data transmission strategy is provided to increase network utilization efficiency, while the data transmission threshold is changed with an adaptive function. This design idea can reduce network transmission pressure more effectively than the traditional one with fixed threshold. Secondly, two independent Bernoulli stochastic sequences are provided to describe the randomly occurring nonlinearity and measured-data packet dropout phenomenon, respectively. By considering time-varying delays, dynamic event-triggered strategy, randomly occurring nonlinearity and packet dropout simultaneously, a unified dynamic model for fault detection is established to generate mean-square asymptotical stability and desirable detection performance. Three examples are finally provided to generate the practicability of proposed technique.