Distributed tracking control of leader-follower multi-agent systems under noisy measurement

TL;DR

This paper presents a distributed control scheme for multi-agent systems that ensures leader tracking despite measurement noise and directed communication, using estimators and a novel velocity decomposition method.

Contribution

It introduces a new distributed tracking control approach with estimators and velocity decomposition for noisy, directed multi-agent systems, ensuring stability and convergence.

Findings

System is stochastically stable in mean square

Estimation errors converge to zero in mean square

Simulation confirms effectiveness of the control scheme

Abstract

In this paper, a distributed tracking control scheme with distributed estimators has been developed for a leader-follower multi-agent system with measurement noises and directed interconnection topology. It is supposed that each follower can only measure relative positions of its neighbors in a noisy environment, including the relative position of the second-order active leader. A neighbor-based tracking protocol together with distributed estimators is designed based on a novel velocity decomposition technique. It is shown that the closed loop tracking control system is stochastically stable in mean square and the estimation errors converge to zero in mean square as well. A simulation example is finally given to illustrate the performance of the proposed control scheme.