Adaptive Intelligent Control for Nonlinear Stochastic Cyber-Physical Systems With Unknown Deception Attacks: Switching Event-Triggered Scheme
Huarong Yue, Jing Zhang, Jianwei Xia, Ju H. Park, Xiangpeng Xie
Abstract
In this paper, the adaptive intelligent control problem for a class of nonlinear switched stochastic cyber-physical systems (CPSs) with output constraint under deception attacks is studied. The output-dependent function is introduced to convert the system into an unconstrained system. In order to eliminate the effects caused by the attacks, the attack gains are introduced into the coordinate transformations and then the Nussbaum function technology is used to deal with the unknown attack gains. Based on the new coordinate transformations, the corresponding controllers are designed for each subsystem using the compromised states. Furthermore, a switching event-triggered mechanism (ETM) is proposed, which can not only resolve asynchronous switching problem without any strict restrictions, but also effectively save communication resources. Meanwhile, a segment constant variable is introduced into the ETM, which is helpful to find a strict positive lower bound for two consecutive triggering intervals to obtain the absence of Zeno behavior. It is shown from the Lyapunov stability theory that all signals in the closed-loop system are bounded in probability under arbitrary switching. Finally, the simulation results validate the effectiveness of the proposed method.