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

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.

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