Distributed Guaranteed-Performance Consensus of Networked Systems Without Involving the Feasibility Condition: A Hierarchical Algorithm

This paper utilizes a hierarchical algorithm to focus on the distributed guaranteed-performance consensus problem of multiagent systems subjected to communication faults. With this algorithm, the consensus problem can be transformed into the tracking problem of agents in adjacent layers, and the constraint range for tracking errors does not depend on the Laplacian matrix of the communication topology. Compared to the existing hierarchical algorithm, a fault-tolerant compensation approach is designed to solve the communication fault between agents. Furthermore, the hierarchical rules are redefined according to the physical significance of topological weights, which enhances the rationality of the partition results. In addition, a shifting function is designed and incorporated into the conventional prescribed performance control approach to eliminate the existing feasibility condition. Based on Lyapunov theory, the sufficient conditions for the boundedness of all signals in the closed-loop system are derived. Finally, two simulation examples verify the efficacy of the scheme.