A secure finite-time consensus scheme for multi-agent systems via terminal iterative learning

In this paper, the secure finite-time consensus problem for distributed multi-agent systems has been studied in the presence of malicious attacks. We give a simple assumption that the maximum number of misbehaving agents in every normal agent's neighborhood is bounded. Contrary to previous approaches, we design secure iterative learning protocol that enables all normal agents to resist the malicious agents and achieve consensus over a finite-time interval if the multi-agent system whose network topology has sufficient connectivity in terms of robustness. Finally, one numerical example is given to demonstrate the effectiveness of our theoretical results.