Title: Adaptive fuzzy model-free control for 3D trajectory tracking of quadrotor

Authors: Zakaria Chekakta; Mokhtar Zerikat; Yasser Bouzid; Anis Koubaa

Addresses: LAAS Laboratory, Department of Electrical Engineering, Ecole Nationale Polytechnique d'Oran Maurice Audin, Oran, Algeria ' LAAS Laboratory, Department of Electrical Engineering, Ecole Nationale Polytechnique d'Oran Maurice Audin, Oran, Algeria ' CSCS Laboratory, Ecole Militaire Polytechnique, Algiers, Algeria ' Robotics and Internet of Things Research Lab, Prince Sultan University, Saudi Arabia

Abstract: This paper presents a novel adaptive control strategy with rejection ability for unmanned aerial vehicles (UAVs), namely fuzzy model-free control (FMFC). It is based on the model-free control (MFC) concept, where the control parameters are tuned online using fuzzy logic. The controller assumes an ultra-local model that can compensate unknown/unmodelled dynamics, uncertainties and external disturbances, ensuring a good robustness level. Moreover, the fuzzy logic system is used to tune online the proportional-derivative terms due to its heuristic aspect. These compensation and adaptation mechanisms allow ensuring good compromise robustness-performance even in the presence of disturbances. Several experiments, using RotorS Gazebo micro aerial vehicle (MAV) simulator, are provided to demonstrate the effectiveness of the proposed controller compared with other techniques. The fuzzy model-free controller shows superior performance without the time-consuming and tedious tuning task.

Keywords: micro aerial vehicle; MAV; model-free control; MFC; fuzzy logic; adaptive control; robust control.

DOI: 10.1504/IJMA.2020.109058

International Journal of Mechatronics and Automation, 2020 Vol.7 No.3, pp.134 - 146

Received: 24 Jan 2020
Accepted: 24 Feb 2020

Published online: 13 Aug 2020 *

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