Event-Triggered Cooperative Adaptive Fuzzy Control for Stochastic Nonlinear Systems With Measurement Sensitivity and Deception Attacks

Abstract

In this article, the leaderless adaptive fuzzy consensus control problem is studied for a class of stochastic nonlinear multiagent systems with unknown measurement sensitivity under false data injection attacks. Unknown measurement sensitivity and false data injection attacks can prevent sensors from obtaining right state information and make it difficult to design controllers and adaptive laws. The existing works considered only one of these cases for deterministic systems. In this article, the coexistence of both cases is considered with the help of Nussbaum functions and fuzzy logic systems, and the corresponding controllers and auxiliary variables are not only codesigned to solve the problem, but also extended to stochastic multiagent systems. Then, an improved switching threshold event-triggered mechanism is proposed to reduce the communication burden of the control channel. Furthermore, the leaderless asymptotic consensus control scheme for stochastic multiagent systems is proposed. The boundedness of all signals and leaderless asymptotic consensus control performance are guaranteed via the Lyapunov stability theorem. Finally, two simulation examples are given to verify the effectiveness of the proposed control scheme.