Security Consensus of Multi-agent Systems under Cyber-attack: An Iterative Learning Control Strategy

This paper focuses on the security consensus problem of multi-agent systems under cyber-attack. Two types of cyber-attack are considered in our research, this situation is more common in real applications. These two types of network attacks (deception and DoS attacks) may occur alternately, resulting in the infeasibility to obtain actual output measurements. To reach the system security, a novel iterative learning control strategy is designed to analyze the issue. Then, sufficient conditions are proposed from the view of the trajectory tracking, and our achieved convergence conditions are relatively simpler in comparison to the existing literature. Furthermore, the theoretical result in this paper is an extension of existing research. Finally, a numerical simulation is presented for illustration.