IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i23p9207-d993843.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/23/9207/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/15/23/9207/
    Download Restriction: no
    ---><---

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Patricio Borbolla-Burillo & David Sotelo & Michael Frye & Luis E. Garza-Castañón & Luis Juárez-Moreno & Carlos Sotelo, 2024. "Design and Real-Time Implementation of a Cascaded Model Predictive Control Architecture for Unmanned Aerial Vehicles," Mathematics, MDPI, vol. 12(5), pages 1-20, February.
    2. Marcin Żugaj & Mohammed Edawdi & Grzegorz Iwański & Sebastian Topczewski & Przemysław Bibik & Piotr Fabiański, 2023. "An Unmanned Helicopter Energy Consumption Analysis," Energies, MDPI, vol. 16(4), pages 1-28, February.
    3. Tukia, Toni & Uimonen, Semen & Siikonen, Marja-Liisa & Donghi, Claudio & Lehtonen, Matti, 2019. "Modeling the aggregated power consumption of elevators – the New York city case study," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    4. Orlando Arrieta & Daniel Campos & Javier Rico-Azagra & Montserrat Gil-Martínez & José D. Rojas & Ramon Vilanova, 2023. "Model-Based Optimization Approach for PID Control of Pitch–Roll UAV Orientation," Mathematics, MDPI, vol. 11(15), pages 1-17, August.
    5. Gorgan, Maxim & Hartvigsen, Morten, 2022. "Development of agricultural land markets in countries in Eastern Europe and Central Asia," Land Use Policy, Elsevier, vol. 120(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9207-:d:993843. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.