Adaptive guaranteed-performance consensus design for high-order multiagent systems

TL;DR

This paper introduces a fully distributed adaptive control strategy for high-order multiagent systems to achieve guaranteed-performance consensus without requiring global topology information, applicable to leaderless and leader-follower structures.

Contribution

It proposes a novel translation-adaptive strategy enabling fully distributed guaranteed-performance consensus control based on the structure of complete graphs.

Findings

Distributed control law ensures guaranteed-performance consensus.

The approach applies to both leaderless and leader-follower multiagent systems.

Numerical examples validate the theoretical results.

Abstract

The current paper addresses the distributed guaranteed-performance consensus design problems for general high-order linear multiagent systems with leaderless and leader-follower structures, respectively. The information about the Laplacian matrix of the interaction topology or its minimum nonzero eigenvalue is usually required in existing works on the guaranteed-performance consensus, which means that their conclusions are not completely distributed. A new translation-adaptive strategy is proposed to realize the completely distributed guaranteed-performance consensus control by using the structure feature of a complete graph in the current paper. For the leaderless case, an adaptive guaranteed-performance consensualization criterion is given in terms of Riccati inequalities and a regulation approach of the consensus control gain is presented by linear matrix inequalities. Extensions to the leader-follower cases are further investigated. Especially, the guaranteed-performance costs for leaderless and leader-follower cases are determined, respectively, which are associated with the intrinsic structure characteristic of the interaction topologies. Finally, two numerical examples are provided to demonstrate theoretical results.