A Novel Edge Laplacian-based Approach for Adaptive Formation Control of Uncertain Multi-agent Systems with Unified Relative Error Performance
Kun Li, Kai Zhao, Yongduan Song, and Lihua Xie

TL;DR
This paper introduces an adaptive formation control method for uncertain multi-agent systems that guarantees prescribed relative error performance using edge Laplacian, simplifying design and ensuring stability.
Contribution
It proposes a novel adaptive control strategy that guarantees prescribed relative error performance with a unified approach, avoiding control redesign and complex initial constraint verification.
Findings
Guarantees prescribed relative error performance via a unified parameter tuning.
Eliminates the need for control redesign under fixed protocols.
Ensures asymptotic stability of the formation manifold.
Abstract
For most existing prescribed performance formation control methods, performance requirements are not directly imposed on the relative states between agents but on the consensus error, which lacks a clear physical interpretation of their solution. In this paper, we propose a novel adaptive prescribed performance formation control strategy, capable of guaranteeing prescribed performance on the relative errors, for uncertain high-order multi-agent systems under a class of directed graphs. Due to the consideration of performance constraints for relative errors, a coupled nonlinear interaction term that contains global graphic information among agents is involved in the error dynamics, leading to a fully distributed control design more difficult and challenging. Here by proposing a series of nonlinear mappings and utilizing the edge Laplacian along with Lyapunov stability theory, the…
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Taxonomy
TopicsDistributed Control Multi-Agent Systems · Neural Networks and Applications · Adaptive Control of Nonlinear Systems
