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Robust Nonlinear Fuzzy Formation Control of Unmanned Quadrotors

by Meisam Khakshour, Nima Nourani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 172 - Number 7
Year of Publication: 2017
Authors: Meisam Khakshour, Nima Nourani
10.5120/ijca2017915179

Meisam Khakshour, Nima Nourani . Robust Nonlinear Fuzzy Formation Control of Unmanned Quadrotors. International Journal of Computer Applications. 172, 7 ( Aug 2017), 18-24. DOI=10.5120/ijca2017915179

@article{ 10.5120/ijca2017915179,
author = { Meisam Khakshour, Nima Nourani },
title = { Robust Nonlinear Fuzzy Formation Control of Unmanned Quadrotors },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2017 },
volume = { 172 },
number = { 7 },
month = { Aug },
year = { 2017 },
issn = { 0975-8887 },
pages = { 18-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume172/number7/28263-2017915179/ },
doi = { 10.5120/ijca2017915179 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:19:42.943840+05:30
%A Meisam Khakshour
%A Nima Nourani
%T Robust Nonlinear Fuzzy Formation Control of Unmanned Quadrotors
%J International Journal of Computer Applications
%@ 0975-8887
%V 172
%N 7
%P 18-24
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A novel leader-following strategy based on fuzzy logic is introduced to design a formation flight controller for unmanned quadrotors. The proposed strategy uses particle swarm optimization (PSO) to optimize the fuzzy membership function in the guidance law, and a nonlinear dynamic inversion (NDI) controller is designed to control the nonlinear dynamics of the quadrotor. The simulation results show the proposed method has significant advantages in comparison with conventional leading-following strategies in terms of robustness against wind gusts, uncertainties, and unknown dynamics.

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Index Terms

Computer Science
Information Sciences

Keywords

Nonlinear control Intelligent systems UAV Optimization.

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