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Open AccessArticle

Pareto Optimal PID Tuning for Px4-Based Unmanned Aerial Vehicles by Using a Multi-Objective Particle Swarm Optimization Algorithm

1
Laboratory of Power and Control Systems (LSPyC), Facultad de Ingeniería, Universidad Nacional de Asunción, Luque 2060, Paraguay
2
Power Electronics and Industrial Control Research Group (GRÉPCI), École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada
*
Author to whom correspondence should be addressed.
Aerospace 2020, 7(6), 71; https://doi.org/10.3390/aerospace7060071
Received: 20 April 2020 / Revised: 19 May 2020 / Accepted: 26 May 2020 / Published: 4 June 2020
(This article belongs to the Collection Unmanned Aerial Systems)
Unmanned aerial vehicles (UAVs) are affordable these days. For that reason, there are currently examples of the use of UAVs in recreational, professional and research applications. Most of the commercial UAVs use Px4 for their operating system. Even though Px4 allows one to change the flight controller structure, the proportional-integral-derivative (PID) format is still by far the most popular choice. A selection of the PID controller parameters is required before the UAV can be used. Although there are guidelines for the design of PID parameters, they do not guarantee the stability of the UAV, which in many cases, leads to collisions involving the UAV during the calibration process. In this paper, an offline tuning procedure based on the multi-objective particle swarm optimization (MOPSO) algorithm for the attitude and altitude control of a Px4-based UAV is proposed. A Pareto dominance concept is used for the MOPSO to find values for the PID comparing parameters of step responses (overshoot, rise time and root-mean-square). Experimental results are provided to validate the proposed tuning procedure by using a quadrotor as a case study. View Full-Text
Keywords: multi-objective particle swarm optimization; Pareto front; proportional-integral-derivative; Px4; quadrotor; unmanned aerial vehicles multi-objective particle swarm optimization; Pareto front; proportional-integral-derivative; Px4; quadrotor; unmanned aerial vehicles
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Gomez, V.; Gomez, N.; Rodas, J.; Paiva, E.; Saad, M.; Gregor, R. Pareto Optimal PID Tuning for Px4-Based Unmanned Aerial Vehicles by Using a Multi-Objective Particle Swarm Optimization Algorithm. Aerospace 2020, 7, 71.

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