Abstract
In this paper, a novel framework for leader-follower formation control is developed for the control of multiple quadrotors 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. © 2009 AACC.
Recommended Citation
T. Dierks and S. Jagannathan, "Neural Network Control of Quadrotor UAV Formations," Proceedings of the American Control Conference, pp. 2990 - 2996, article no. 5160591, Institute of Electrical and Electronics Engineers, Nov 2009.
The definitive version is available at https://doi.org/10.1109/ACC.2009.5160591
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
Keywords and Phrases
Formation control; Lyapunov stability; Neural networks; Quadrotor UAV
International Standard Book Number (ISBN)
978-142444524-0
International Standard Serial Number (ISSN)
0743-1619
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
23 Nov 2009
