4.7 Article

Flocking of Multi-Agents With a Virtual Leader

Journal

IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume 54, Issue 2, Pages 293-307

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2008.2010897

Keywords

Distributed control; flocking; informed agents; nonlinear systems; virtual leader

Funding

  1. National Natural Science Foundation of China [60521002, 70431002, 60674045, 60428303]

Ask authors/readers for more resources

All agents being informed and the virtual leader traveling at a constant velocity are the two critical assumptions seen in the recent literature on Hocking in multi-agent systems. Under these assumptions, Olfati-Saber in a recent IEEE TRANSACTIONS ON AUTOMATIC CONTROL paper proposed a flocking algorithm which by incorporating a navigational feedback enables a group of agents to track a virtual leader. This paper revisits the problem of multiagent flocking in the absence of the above two assumptions. We first show that, even when only a fraction of agents are informed, the Olfati-Saber Hocking algorithm still enables all the informed agents to move with the desired constant velocity, and an uninformed agent to also move with the same desired velocity if it can be influenced by the informed agents from time to time during the evolution. Numerical simulation demonstrates that a very small group of the informed agents can cause most of the agents to move with the desired velocity and the larger the informed group is the bigger portion of agents will move with the desired velocity. In the situation where the virtual leader travels with a varying velocity, we propose modification to the Olfati-Saber algorithm and show that the resulting algorithm enables the asymptotic tracking of the virtual leader. That is, the position and velocity of the center of mass of all agents will converge exponentially to those of the virtual leader. The convergent rate is also given.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available