An Event-Triggered Fault Detection Approach in Cyber-Physical Systems with Sensor Nonlinearities and Deception Attacks

Abstract

In this paper, a general event-triggered framework is constructed to investigate the problem of remote fault detection for stochastic cyber-physical systems subject to the additive disturbances, sensor nonlinearities and deception attacks. Both fault-detection residual generation and evaluation module are fully described. Two energy norm indices are presented so that the fault-detection residual has the best sensitivity to faults and the best robustness to unwanted factors including additive disturbances and false information injected by attacker. Moreover, the filter gain and residual weighting matrix are formulated in terms of stochastic Lyapunov function, which can be conveniently solved via standard numerical software. Finally, an application example is presented to verify the performance of fault detection by comparative simulations. The prolonged battery life is experimentally evaluated and analyzed via a wireless node platform.

Recent Developments in Time-Delay Systems and Their Applications

“…As for networked control systems, some significant issues are addressed: the impact of delays on network-based systems for droop-controlled AC microgrid is investigated in Reference [8]; Tracking control for cloud robotic systems with delayed measurements is considered in Reference [9]; An event-triggered fault detection approach to cyber-physical systems with sensor nonlinearities and deception attacks is presented in Reference [10]; and a non-standard discretization method is introduced to stability analysis of sampled-data systems in Reference [11].…”

Adaptive Threshold Generation for Fault Detection with High Dependability for Cyber-Physical Systems

“…In change detection, using a threshold is known as a send-on-delta (SoD) technique [18][19][20][21][22][23]. After a SoD-enabled system uses the predefined thresholds, referred to as delta, to detect significant changes for measurement, it reports the detected event.…”

“…To cope with both the nonlinearity caused by the environment uncertainty and the attacks injected through the network, the SoD method is employed to detect attacks for the generated residual after a detection filter is designed with the residual weight and the filter gain [23]. Since it is assumed that noise follows the Gaussian distribution due to network environments, it is difficult to guarantee performance in an environment where the distribution is unknown.…”

Observer‐Based Sensor Attack Diagnosis for Cyber‐Physical Systems via Zonotope Theory

“…Estimating the values of the attack signals is called attack reconstruction. In fact, sensor attack detection and fault tolerant control against the attack in order that the negative effects can be suppressed greatly becomes one of the major considerations in a CPS design [28][29][30][31][32][33][34][35][36]. For example, [28] proposes a design methodology based on sliding-mode techniques for building a state/sensor attack observer used as a detection monitor, and reconstructing the attack itself in the presence of bounded external perturbations or mode uncertainties.…”