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Adaptive trajectory tracking control strategy of intelligent vehicle

Author

Listed:
  • Shuo Zhang
  • Xuan Zhao
  • Guohua Zhu
  • Peilong Shi
  • Yue Hao
  • Lingchen Kong

Abstract

The trajectory tracking control strategy for intelligent vehicle is proposed in this article. Considering the parameters perturbations and external disturbances of the vehicle system, based on the vehicle dynamics and the preview follower theory, the lateral preview deviation dynamics model of the vehicle system is established which uses lateral preview position deviation, lateral preview velocity deviation, lateral preview attitude angle deviation, and lateral preview attitude angle velocity deviation as the tracking state variables. For this uncertain system, the adaptive sliding mode control algorithm is adopted to design the preview controller to eliminate the effects of uncertainties and realize high accuracy of the target trajectory tracking. According to the real-time deviations of lateral position and lateral attitude angle, the feedback controller is designed based on the fuzzy control algorithm. For improving the adaptability to the multiple dynamic states, the extension theory is introduced to design the coordination controller to adjusting the control proportions of the preview controller and the feedback controller to the front wheel steering angle. Simulation results verify the adaptability, robustness, accuracy of the control strategy under which the intelligent vehicle has good handling stability.

Suggested Citation

  • Shuo Zhang & Xuan Zhao & Guohua Zhu & Peilong Shi & Yue Hao & Lingchen Kong, 2020. "Adaptive trajectory tracking control strategy of intelligent vehicle," International Journal of Distributed Sensor Networks, , vol. 16(5), pages 15501477209, May.
    • Handle: RePEc:sae:intdis:v:16:y:2020:i:5:p:1550147720916988
    DOI: 10.1177/1550147720916988
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    References listed on IDEAS

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    1. Younés Abbassi & Youcef Ait-Amirat & Rachid Outbib, 2015. "Nonlinear feedback control and trajectory tracking of vehicle," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(16), pages 2873-2886, December.
    2. Peng Wang & Qingyun Wang & Maosong Wan & Ning Chen, 2018. "A Fractional Derivative-Based Lateral Preview Driver Model for Autonomous Automobile Path Tracking," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-9, September.
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    Cited by:

    1. Adnan Khalid & Mujtaba Hussain Jaffery & Muhammad Yaqoob Javed & Adnan Yousaf & Jehangir Arshad & Ateeq Ur Rehman & Aun Haider & Maha M. Althobaiti & Muhammad Shafiq & Habib Hamam, 2021. "Performance Analysis of Mars-Powered Descent-Based Landing in a Constrained Optimization Control Framework," Energies, MDPI, vol. 14(24), pages 1-14, December.

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