Distributed adaptive formation control of multi-agent systems with measurement noises

In this paper, we investigate the distributed adaptive formation control problem of leader-following multi-agent systems where the measurements are subject to noises. A distributed LMS-like algorithm is proposed to estimate the relative position between the followers and the leader. By employing the “certainty equivalence” principle, an adaptive motion controller is designed to achieve the desired formation under dynamically changing interaction topologies. The incompatibility in simultaneously satisfying the persistent excitation condition required by localization estimators and accomplishing the control tasks makes the theoretical analysis challenging. In order to deal with this issue, an excited noise signal is embedded into the control law. We give the upper bounds of both the estimation errors and formation error of the closed-loop multi-agent system under the distributed adaptive control law. Finally, the numerical simulations are provided to demonstrate the effectiveness of our theoretical results.