Robust RCF-based Leader-Following Consensus for Uncertain Multi-Agent Systems

This paper proposes a novel robust control scheme based on right coprime factorization (RCF) to address the consensus control problem for multi-agent systems with communication delays, measurement noise, and uncertainties. First, the communication topology with single-leader-driven multi-branch unidirectional chain is formalized, and each uncertain agent’s model is factorized using RCF theory. Then, a compensator is designed to mitigate the effects of communication delays and measurement noise. Based on the Bezout identity, a feedback system is constructed, complemented by two operators. Subsequently, an additional controller is developed to achieve the desired consensus performance, supported by theoretical feasibility analysis. Finally, the effectiveness and robustness are demonstrated through a multi-agent soft robotic finger system.