Event-Triggered Fault Detection in Networked Control Systems
Summary
Networked control systems interconnect spatially distributed sensors, actuators and controllers via communication networks. Fault detection within such systems must reconcile the competing demands of timely anomaly identification and efficient use of limited network bandwidth. Event-triggered strategies address this challenge by transmitting data only when a predefined condition is met, rather than at fixed intervals. A typical arrangement employs an observer or filter at the controller node that generates a residual signal— the discrepancy between predicted and actual measurements. When this residual exceeds a time-varying threshold, a transmission is triggered to refine fault estimates or to raise an alarm. Such schemes can integrate H∞ design principles to balance disturbance rejection with fault sensitivity and may employ Lyapunov–Krasovskii functionals to account for time-delays and packet dropouts. The approach has been applied to diverse platforms—from automotive lateral-dynamics models to industrial process loops—and shows promise in reducing communication load by up to an order of magnitude while sustaining reliable detection of sensor, actuator or cyber-attack faults.
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Event-Triggered Fault Detection in Networked Control Systems publication trend
The graph below shows the total number of articles in event-triggered fault detection in networked control systems across all publications each year (not limited to Nature Index journals).
Technical terms
Event-triggering mechanism: A rule that determines when sensor or observer data should be transmitted based on the system’s state or estimation error exceeding a threshold.
Residual: The difference between measured outputs and observer-predicted outputs, used to detect anomalies indicating faults.
Diagnostic observer: An algorithmic construct that estimates system states and fault signals remotely, often designed to be robust to disturbances and network uncertainties.
Lyapunov–Krasovskii functional: A generalised energy-like measure that provides stability conditions for time-delay systems, essential for analysing event-triggered schemes.
False data injection attack: A cyber-attack in which an adversary corrupts sensor or actuator data to deceive the fault detection mechanism, modelled as a stochastic process in advanced designs.
References
- Event-Triggered Diagnostic Observer Design Using the Performance Tradeoff Approach. IEEE Access (2022).
- Dynamic Event-Triggered Fault Detection for Discrete Networked Control System With Time-Delay. IEEE Access (2022).
- Event-Triggered Fault Estimation and Fault Tolerance for Cyber-Physical Systems with False Data Injection Attacks. Actuators (2023).
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