Title: Intelligent PSO-based PDs/PIDs controllers for an unmanned quadrotor

Authors: Nada El Gmili; Mostafa Mjahed; Abdeljalil El Kari; Hassan Ayad

Addresses: Department of Applied Physics, Cadi Ayyad University, Marrakesh, Morocco ' Department of Mathematics and Systems, Royal School of Aeronautics, Marrakesh, Morocco ' Department of Applied Physics, Cadi Ayyad University, Marrakesh, Morocco ' Department of Applied Physics, Cadi Ayyad University, Marrakesh, Morocco

Abstract: This paper presents intelligent PDs/PIDs controllers based on particle swarm optimisation (PSO) for an unmanned aerial vehicle (UAV) quadrotor. Because of physical effect, the aircraft dynamics' nature is fully coupled and strongly nonlinear. Firstly, the mathematical model is derived using Newton-Euler formalism. Based on this model, a nonlinear control scheme, incorporating six PDs/PIDs controllers, is developed to control the position (x and y), the altitude z and the attitude (ϕ, θ and ψ angles). Secondly, the metaheuristic particle swarm optimisation (PSO) and the conventional reference model (RM) techniques are applied to tune the PDs and PIDs gains for the aircraft stability. Finally, diverse simulations using MATLAB prove that PD-PSO is more suitable and efficient for the quadrotor control. Indeed, its robustness is demonstrated in the presence of wind disturbances.

Keywords: quadrotor; nonlinear; UAV; PD; PID; controllers; particle swarm optimisation; PSO; reference model; control; stabilisation; trajectory tracking; intelligent engineering.

DOI: 10.1504/IJIEI.2018.096579

International Journal of Intelligent Engineering Informatics, 2018 Vol.6 No.6, pp.548 - 568

Received: 22 Jun 2018
Accepted: 03 Sep 2018

Published online: 05 Dec 2018 *

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