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A Novel LCOT Control Strategy for Self-Driving Electric Mobile Robots

Author

Listed:
  • Hwa-Dong Liu

    (Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taipei 106, Taiwan)

  • Guo-Jyun Gao

    (Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taipei 106, Taiwan)

  • Shiue-Der Lu

    (Department of Electrical Engineering, National Chin-Yi University of Technology, Taichung 411, Taiwan)

  • Yi-Hsuan Hung

    (Undergraduate Program of Vehicle and Energy Engineering, National Taiwan Normal University, Taipei 106, Taiwan)

Abstract

This study proposes a novel logarithm curve and operating time (LCOT) control strategy for a self-driving electric mobile robot. This new LCOT control strategy enables the mobile robot to speed up and slow down mildly when running longitudinally, turning left, turning right, and encountering an obstacle based on the relationship between the logarithm curve and operating time. This novel control strategy can enhance the comfort and stability of the self-driving electric mobile robot and reduce its vibrations and instabilities in the operation process. The proposed LCOT control strategy and the fixed duty cycle method were verified experimentally. The results showed that the LCOT control strategy spent 300 s running on a 3000 cm road, whereas the fixed duty cycle method spent 450 s. Because this novel method controls the acceleration and deceleration of the self-driving electric mobile robot gently and flexibly, the proposed LCOT control strategy has better working efficiency than the fixed duty cycle method. This novel control strategy is simple and easy to be implemented. As it can reduce the working load of the controller, increase system efficiency, and require low cost, it can be effectively used in a self-driving electric mobile robot.

Suggested Citation

  • Hwa-Dong Liu & Guo-Jyun Gao & Shiue-Der Lu & Yi-Hsuan Hung, 2022. "A Novel LCOT Control Strategy for Self-Driving Electric Mobile Robots," Energies, MDPI, vol. 15(23), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9178-:d:992623
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    References listed on IDEAS

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    1. Seppo Borenius & Petri Tuomainen & Jyri Tompuri & Jesse Mansikkamäki & Matti Lehtonen & Heikki Hämmäinen & Raimo Kantola, 2022. "Scenarios on the Impact of Electric Vehicles on Distribution Grids," Energies, MDPI, vol. 15(13), pages 1-30, June.
    2. Anatolii Nikitenko & Mykola Kostin & Tetiana Mishchenko & Oksana Hoholyuk, 2022. "Electrodynamics of Power Losses in the Devices of Inter-Substation Zones of AC Electric Traction Systems," Energies, MDPI, vol. 15(13), pages 1-18, June.
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    1. Adam Szeląg & Mladen Nikšić, 2023. "Advances in Electric Traction System—Special Issue," Energies, MDPI, vol. 16(3), pages 1-5, January.

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