Finite-Time Fault Detection for Uncertain Delayed Systems with Packet Dropouts Under Adaptive Event-Triggered Mechanism

The rapid advancement of industrial informatization and communication technology has led to the widespread adoption of communication networks in various industrial systems, including power systems, unmanned aerial vehicles, and high-speed train traction systems. However, these networked systems are susceptible to harsh environments and electromagnetic interference, which can result in system faults. This article delves into the finite-time fault detection (FD) problem for uncertain delayed systems, addressing the challenges posed by packet dropouts, distributed delays, and nonlinearities. It introduces an adaptive event-triggered mechanism (AETM) that dynamically adjusts the triggered threshold based on the error between the latest transmitted data and the current data, improving data transmission efficiency and fault detection performance. The article provides sufficient criteria for the existence of a fault detection filter (FDF) that ensures the residual system satisfies finite-time stochastic stability and a prescribed performance index. A simulation example using a networked DC motor system demonstrates the effectiveness of the proposed FD method, highlighting its potential for enhancing the performance and safety of industrial systems.