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<p>In order to ensure that vehicle can also have good path tracking performance during braking or acceleration process, A fractional order sliding mode controller with two fractional order terms is proposed for path tracking control. First, a three-degree-of-freedom dynamic model is established, and the tire force calculation formula based on Dugoff tire model is given. Based on the kinematic model and the error state equation of vehicle path tracking, a sliding mode controller for vehicle path tracking is designed, the quadratic performance index optimization method is used to obtain the sliding mode surface coefficient. And the fractional calculus is introduced to improve it into fractional order sliding mode surface and fractional order reaching rate sliding mode control, in order to cope with the time-varying characteristics of the system and the change of other parameters in the model when the vehicle changes speed. Finally, MATLAB and Carsim platform are used for co-simulation to verify the double fractional-order sliding mode controller. The results show that compared with the commonly used LQR and MPC controllers, the double fractional-order sliding mode controller has a more ideal path tracking ability under braking and acceleration conditions.</p>

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Research on sliding mode control for path following in variable speed of unmanned vehicle

  • 期刊论文

  • 发表日期：

    2025年1月30日

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  • Jian Zhang,
  • Min Yang,
  • Yandong Chen,
  • Hongyu Li,
  • Ning Chen,
  • Yong Zhang

摘要

In order to ensure that vehicle can also have good path tracking performance during braking or acceleration process, A fractional order sliding mode controller with two fractional order terms is proposed for path tracking control. First, a three-degree-of-freedom dynamic model is established, and the tire force calculation formula based on Dugoff tire model is given. Based on the kinematic model and the error state equation of vehicle path tracking, a sliding mode controller for vehicle path tracking is designed, the quadratic performance index optimization method is used to obtain the sliding mode surface coefficient. And the fractional calculus is introduced to improve it into fractional order sliding mode surface and fractional order reaching rate sliding mode control, in order to cope with the time-varying characteristics of the system and the change of other parameters in the model when the vehicle changes speed. Finally, MATLAB and Carsim platform are used for co-simulation to verify the double fractional-order sliding mode controller. The results show that compared with the commonly used LQR and MPC controllers, the double fractional-order sliding mode controller has a more ideal path tracking ability under braking and acceleration conditions.