Neural network control of quadrotor UAV formations

Authors:
Travis Dierks;S. Jagannathan
Affiliations:
Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO;Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla, MO
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

Citing 2
Cited 2

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Decentralized Perimeter Surveillance Using a Team of UAVs

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Experimental test of an interacting multiple model filtering algorithm for actuator fault detection and diagnosis of an unmanned quadrotor helicopter

ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
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Journal of Intelligent and Robotic Systems

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Abstract

In this paper, a novel framework for leader-follower formation control is developed for the control of multiple quadrotor unmanned aerial vehicles (UAVs) based on spherical coordinates. The control objective for the follower UAV is to track its leader at a desired- separation, angle of incidence, and a bearing by using an auxiliary velocity control. Then, a novel neural network (NN) control law for the dynamical system is introduced to learn the complete dynamics of the UAV including unmodeled dynamics like aerodynamic friction. Additionally, the interconnection dynamic errors between the leader and its followers are explicitly considered, and the stability of the entire formation is demonstrated using Lyapunov theory. Numerical results verify the theoretical conjectures.