Distributed Secure Consensus Tracking for Multi-Agent Systems: From Asymptotic to finite-/fixed-Time Convergence

This paper investigates the problem of distributed secure consensus tracking for leader-following multi-agent systems under the presence of sparse data anomalies in the networks. An extra auxiliary function is designed and employed to formulate the interaction gains to mitigate the impact of such unknown sparse anomalies. Different from conventional anomaly detection and isolation methods, the introduction of the auxiliary function can alleviate the wasteful expansion of global sparse anomaly detectors and facilitate non-smooth control. Consequently, we formulate a new design framework for secure consensus protocols, enabling all followers to realize asymptotic and even finite-/fixed-time tracking to the leader. Finally, some simulation examples are presented to illustrate the effectiveness of the theoretical results.