Decentralized aggregation and leader-following control of a swarm of quadcopters with nonlinear under-actuated dynamics

Abstract

This paper studies the decentralized control of a swarm of quadrotors on the basis of the nonlinear, highly-coupled, and under-actuated dynamic model of quadcopters. The swarm of quadcopters must illustrate the desired swarm behavior as fast as possible while collision avoidance is preserved during the entire evolution process. The interaction relationship among the swarm members is modeled by artificial potential functions and according to the nearest neighbor rule. The sliding mode control technique is employed to control the velocity of quadcopters in the swarm. Finally, two fundamental swarm behaviors, i.e. swarm aggregation and leader-following, are numerically simulated to demonstrate the efficacy of the proposed algorithm.