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On Obtaining Energy-Optimal Trajectories for Landing of UAVs

Author

Listed:
  • Dariusz Horla

    (Institute of Robotics and Machine Intelligence, Faculty of Control Robotics and Electrical Engineering, Poznan University of Technology, ul. Piotrowo 3a, 60-965 Poznan, Poland)

  • Jacek Cieślak

    (Institute of Robotics and Machine Intelligence, Faculty of Control Robotics and Electrical Engineering, Poznan University of Technology, ul. Piotrowo 3a, 60-965 Poznan, Poland)

Abstract

The optimization issues connected to a landing task of an unmanned aerial vehicle are discussed in the paper, based on a model of a mini-class drone. Three landing scenarios are considered, including minimum-time landing, landing with minimum energy consumption, and planned landing. With the use of classical dynamic programming techniques, including the minimum principle of Pontryagin, as well as the calculus of variations, the optimal altitude reference trajectories are found, to form the altitude control system in such a way as to mimic the profile of the reference trajectory by the actual altitude of the UAV. The simulation results conducted with the use of the Simulink Support Package for Parrot Minidrones verify the correctness and effectiveness of the method, and open the research directions for further analysis, especially to tune altitude controller in a way, as to track the reference profile. Up to this point, optimization tasks considered in the literature, with respect to the drones, were connected to swarm formation optimization, optimization of the take-off process or landing process limited to optimal path planning. This paper thus considers a new topic in the field.

Suggested Citation

  • Dariusz Horla & Jacek Cieślak, 2020. "On Obtaining Energy-Optimal Trajectories for Landing of UAVs," Energies, MDPI, vol. 13(8), pages 1-25, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:2062-:d:348097
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    Citations

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    Cited by:

    1. Yanxiang Yang & Xiangyin Zhang & Jiayi Zhou & Bo Li & Kaiyu Qin, 2022. "Global Energy Consumption Optimization for UAV Swarm Topology Shaping," Energies, MDPI, vol. 15(7), pages 1-21, March.
    2. Piotr Szeląg & Sebastian Dudzik & Anna Podsiedlik, 2023. "Investigation on the Mobile Wheeled Robot in Terms of Energy Consumption, Travelling Time and Path Matching Accuracy," Energies, MDPI, vol. 16(3), pages 1-30, January.
    3. Maciej Podsędkowski & Rafał Konopiński & Damian Obidowski & Katarzyna Koter, 2020. "Variable Pitch Propeller for UAV-Experimental Tests," Energies, MDPI, vol. 13(20), pages 1-16, October.
    4. Kazuki Nonoyama & Ziang Liu & Tomofumi Fujiwara & Md Moktadir Alam & Tatsushi Nishi, 2022. "Energy-Efficient Robot Configuration and Motion Planning Using Genetic Algorithm and Particle Swarm Optimization," Energies, MDPI, vol. 15(6), pages 1-20, March.

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