Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor
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 dynami...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/5/2143 |
| _version_ | 1797615458598256640 |
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| author | Mohamed Elhesasy Tarek N. Dief Mohammed Atallah Mohamed Okasha Mohamed M. Kamra Shigeo Yoshida Mostafa A. Rushdi |
| author_facet | Mohamed Elhesasy Tarek N. Dief Mohammed Atallah Mohamed Okasha Mohamed M. Kamra Shigeo Yoshida Mostafa A. Rushdi |
| author_sort | Mohamed Elhesasy |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T07:26:37Z |
| format | Article |
| id | doaj.art-8bcd7f7414d24cf9a9371168cf9bc4cd |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T07:26:37Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-8bcd7f7414d24cf9a9371168cf9bc4cd2023-11-17T07:34:44ZengMDPI AGEnergies1996-10732023-02-01165214310.3390/en16052143Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of QuadrotorMohamed Elhesasy0Tarek N. Dief1Mohammed Atallah2Mohamed Okasha3Mohamed M. Kamra4Shigeo Yoshida5Mostafa A. Rushdi6College of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab EmiratesCollege of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab EmiratesCollege of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab EmiratesCollege of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab EmiratesCollege of Engineering, UAE University, Al-Ain P.O. Box 15551, United Arab EmiratesResearch Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka 816-8580, JapanResearch Institute for Applied Mechanics (RIAM), Kyushu University, Fukuoka 816-8580, JapanIn 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.https://www.mdpi.com/1996-1073/16/5/2143model predictive control (MPC)non-linear MPC (NLMPC)CasADiquadrotorPIDSimulink |
| spellingShingle | Mohamed Elhesasy Tarek N. Dief Mohammed Atallah Mohamed Okasha Mohamed M. Kamra Shigeo Yoshida Mostafa A. Rushdi Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor Energies model predictive control (MPC) non-linear MPC (NLMPC) CasADi quadrotor PID Simulink |
| title | Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor |
| title_full | Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor |
| title_fullStr | Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor |
| title_full_unstemmed | Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor |
| title_short | Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor |
| title_sort | non linear model predictive control using casadi package for trajectory tracking of quadrotor |
| topic | model predictive control (MPC) non-linear MPC (NLMPC) CasADi quadrotor PID Simulink |
| url | https://www.mdpi.com/1996-1073/16/5/2143 |
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