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Stability of Interval Type-3 Fuzzy Controllers for Autonomous Vehicles

Author

Listed:
  • Man-Wen Tian

    (National Key Project Laboratory, Jiangxi University of Engineering, Xinyu 338000, China)

  • Shu-Rong Yan

    (National Key Project Laboratory, Jiangxi University of Engineering, Xinyu 338000, China)

  • Ardashir Mohammadzadeh

    (Electrical Engineering Department, University of Bonab, Bonab 5551395133, Iran)

  • Jafar Tavoosi

    (Department of Electrical Engineering, Ilam University, Ilam 69315516, Iran)

  • Saleh Mobayen

    (Future Technology Research Center, National Yunlin University of Science and Technology, Douliu 64002, Taiwan)

  • Rabia Safdar

    (Department of Mathematics, Lahore College Women University, Lahore 54000, Pakistan)

  • Wudhichai Assawinchaichote

    (Department of Electronic and Telecommunication Engineering, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand)

  • Mai The Vu

    (School of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Korea)

  • Anton Zhilenkov

    (Department of Cyber-Physical Systems, St. Petersburg State Marine Technical University, 190121 Saint-Petersburg, Russia)

Abstract

Economic efficient Autonomous Road Vehicles (ARVs) are invariably subjected to uncertainties and perturbations. Therefore, control of vehicle systems requires stability to withstand the effect of variations in the nominal performance. Lateral path-tracking is a substantial task of ARVs, especially in critical maneuvering and cornering with variable speed. In this study, a new controller on the basis of interval type-3 (T3) fuzzy logic system (FLSs) is designed. The main novelties and advantages are as follows. (1) The uncertainty is a main challenge in the path-following problem of ARVs. However, in the fuzzy-based approaches, the bounds of uncertainty are assumed to be known. However, in the our suggested approach, the bounds of uncertainties are also fuzzy sets and type-3 FLSs with online adaptation rules are suggested to handle the uncertainties. (2) The approximation errors (AEs) and perturbations are investigated and tackled by the compensators. (3) The bounds of estimation errors are also uncertain and are estimated by the suggested adaptation laws. (4) The stability is ensured under unknown dynamics, perturbations and critical maneuvers. (5) Comparison with the benchmarking techniques and conventional fuzzy approaches verifies that the suggested path-following scheme results in better maneuver performance.

Suggested Citation

  • Man-Wen Tian & Shu-Rong Yan & Ardashir Mohammadzadeh & Jafar Tavoosi & Saleh Mobayen & Rabia Safdar & Wudhichai Assawinchaichote & Mai The Vu & Anton Zhilenkov, 2021. "Stability of Interval Type-3 Fuzzy Controllers for Autonomous Vehicles," Mathematics, MDPI, vol. 9(21), pages 1-17, October.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:21:p:2742-:d:666981
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    References listed on IDEAS

    as
    1. Tian, Man-Wen & Talebizadehsardari, Pouyan, 2021. "Energy cost and efficiency analysis of building resilience against power outage by shared parking station for electric vehicles and demand response program," Energy, Elsevier, vol. 215(PB).
    2. Cheng-Hung Chen & Shiou-Yun Jeng & Cheng-Jian Lin, 2020. "Mobile Robot Wall-Following Control Using Fuzzy Logic Controller with Improved Differential Search and Reinforcement Learning," Mathematics, MDPI, vol. 8(8), pages 1-21, July.
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