Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor
Author:
Elhesasy Mohamed1ORCID, Dief Tarek N.1, Atallah Mohammed1ORCID, Okasha Mohamed1ORCID, Kamra Mohamed M.1, Yoshida Shigeo23ORCID, Rushdi Mostafa A.2
Affiliation:
1. College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates 2. Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka 816-8580, Japan 3. Institute of Ocean Energy (IOES), Saga University, Saga 840-8502, Japan
Abstract
In this paper, we present the development of a non-linear model predictive controller for the trajectory tracking of a quadrotor using the CasADi optimization framework. The non-linear dynamic model of the quadrotor was derived using Newton–Euler equations, and the control algorithm and drone dynamics were wrapped in Matlab. The proposed controller was tested by simulating the tracking of a 3D helical reference trajectory, and its efficiency was evaluated in terms of numerical performance and tracking accuracy. The results showed that the proposed controller leads to faster computational times, approximately 20 times faster than the Matlab toolbox (nlmpc), and provides better tracking accuracy than both the Matlab toolbox and classical PID controller. The robustness of the proposed control algorithm was also tested and verified under model uncertainties and external disturbances, demonstrating its ability to effectively eliminate tracking errors.
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
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