Distributed Consensus of Feedforward Nonlinear Stochastic Multiagent Systems Subject to Actuator Attacks
研究了有向固定拓扑下，执行器遭受欺骗攻击的前馈非线性随机多智能体系统的分布式领导者跟随全状态一致性问题，提出了一种新型攻击模型和输出反馈一致性控制算法。
This article explores the distributed leader-following full-state consensus control problem for feedforward nonlinear stochastic multiagent system with actuator deception attacks under a fixed directed topology. Unlike the existing works, we establish a novel actuator deception attack model, the attacks have higher stealthiness in model. The false injection information of the attack is generated by a stochastic inverse dynamics system satisfying the stochastic input-to-state stable condition, and the input of the system depends on the relevant output information of neighboring agents, rather than all state information. In this case, we develop a novel distributed output feedback consensus control algorithm to overcome the impact of attacks and stochastic disturbances. First, we design the distributed linear controller with a compensator for each follower based on the relevant outputs, and provide sufficient conditions for ensuring its effectiveness. Then, we construct a new candidate Lyapunov function with a power constant that is used to relax the constraints of the attack model. Subsequently, by means of the exchanging supply function approach, we strictly prove that all agents can achieve leader-following full-state bounded consensus in probability. Finally, an illustrative simulation is provided to showcase the efficacy of our methodology.