Decentralized control of multiple unmanned aircraft for target tracking and obstacle avoidance

A decentralized controller for target tracking and obstacle avoidance for a multi-agent system is proposed. The controller is based on a navigation function which is composed of a goal function, as the D-optimality criterion of the Fisher information matrix, and a constraint function, which generates repulsive force to the agents near the obstacle. The multi-agent system is modeled as a graph and each agent moves independently by the control input calculated based on the information accessible for the agent. It is proved that the multi-agent system converges to the critical points where the navigation function achieves its global minimum by acquiring maximum information of the target while avoiding collision with the target. An exemplary simulation study is given for a multiple unmanned aircraft system.

I. Introduction

Decentralized controllers have been developed for various applications which require collaborative motion of a group of agents. The decentralized control approach is generally designed to guarantee that a multi-agent system, modeled as a graph, can form a desired configuration while avoiding collisions with other agents and obstacles [1]–[4]. Furthermore, [4]–[7] consider network objectives, such as formation control, consensus, and network connectivity, as well as obstacle avoidance. For achieving the goal, a navigation function, as a particular class of potential functions, is adopted to design the controller [8], [9]. The controller is required to guarantee that the agents within the navigation function can act independently to make the function converge to the global minimum.