LAPSE:2023.20214
Published Article

LAPSE:2023.20214
Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor
March 17, 2023
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.
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.
Record ID
Keywords
CasADi, model predictive control (MPC), non-linear MPC (NLMPC), PID, quadrotor, Simulink
Subject
Suggested Citation
Elhesasy M, Dief TN, Atallah M, Okasha M, Kamra MM, Yoshida S, Rushdi MA. Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor. (2023). LAPSE:2023.20214
Author Affiliations
Elhesasy M: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates [ORCID]
Dief TN: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates
Atallah M: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates [ORCID]
Okasha M: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates [ORCID]
Kamra MM: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates
Yoshida S: Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka 816-8580, Japan; Institute of Ocean Energy (IOES), Saga University, Saga 840-8502, Japan [ORCID]
Rushdi MA: Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka 816-8580, Japan [ORCID]
Dief TN: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates
Atallah M: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates [ORCID]
Okasha M: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates [ORCID]
Kamra MM: College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab Emirates
Yoshida S: Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka 816-8580, Japan; Institute of Ocean Energy (IOES), Saga University, Saga 840-8502, Japan [ORCID]
Rushdi MA: Research Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka 816-8580, Japan [ORCID]
Journal Name
Energies
Volume
16
Issue
5
First Page
2143
Year
2023
Publication Date
2023-02-22
ISSN
1996-1073
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Original Submission
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PII: en16052143, Publication Type: Journal Article
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LAPSE:2023.20214
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https://doi.org/10.3390/en16052143
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Mar 17, 2023
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