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Towards Optimization of Energy Consumption of Tello Quad-Rotor with Mpc Model Implementation

Author

Listed:
  • Rabab Benotsmane

    (Institute of Automation and Info-Communication, University of Miskolc (UM), 3515 Miskolc, Hungary)

  • József Vásárhelyi

    (Institute of Automation and Info-Communication, University of Miskolc (UM), 3515 Miskolc, Hungary)

Abstract

For the last decade, there has been great interest in studying dynamic control for unmanned aerial vehicles, but drones—although a useful technology in different areas—are prone to several issues, such as instability, the high energy consumption of batteries, and the inaccuracy of tracking targets. Different approaches have been proposed for dealing with nonlinearity issues, which represent the most important features of this system. This paper focuses on the most common control strategy, known as model predictive control (MPC), with its two branches, linear (LMPC) and nonlinear (NLMPC). The aim is to develop a model based on sensors embedded in a Tello quad-rotor used for indoor purposes. The original controller of the Tello quad-rotor is supposed to be the slave, and the designed model predictive controller was created in MATLAB. The design was imported to another embedded system, considered the master. The objective of this model is to track the reference trajectory while maintaining the stability of the system and ensuring low energy consumption. The case study in this paper compares linear and nonlinear model predictive control (MPC). The results show the efficiency of NLMPC, which provides more promising results compared to LMPC. The comparison concentrates on the energy consumption, the tracked trajectory, and the execution time. The main finding of this research is that NLMPC is a good solution to smoothly track the reference trajectory. The controller in this case processes faster, but the rotors consume more energy because of the increased values of control inputs calculated by the nonlinear controller.

Suggested Citation

  • Rabab Benotsmane & József Vásárhelyi, 2022. "Towards Optimization of Energy Consumption of Tello Quad-Rotor with Mpc Model Implementation," Energies, MDPI, vol. 15(23), pages 1-25, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9207-:d:993843
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    References listed on IDEAS

    as
    1. Xiaodong Zhang & Xiaoli Li & Kang Wang & Yanjun Lu, 2014. "A Survey of Modelling and Identification of Quadrotor Robot," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-16, October.
    2. Mariusz Jacewicz & Marcin Żugaj & Robert Głębocki & Przemysław Bibik, 2022. "Quadrotor Model for Energy Consumption Analysis," Energies, MDPI, vol. 15(19), pages 1-33, September.
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    Citations

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    Cited by:

    1. Mohamed Elhesasy & Tarek N. Dief & Mohammed Atallah & Mohamed Okasha & Mohamed M. Kamra & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Non-Linear Model Predictive Control Using CasADi Package for Trajectory Tracking of Quadrotor," Energies, MDPI, vol. 16(5), pages 1-17, February.
    2. Rabab Benotsmane & György Kovács, 2023. "Optimization of Energy Consumption of Industrial Robots Using Classical PID and MPC Controllers," Energies, MDPI, vol. 16(8), pages 1-28, April.

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