Research on trajectory tracking of unmanned vehicle based on model predictive control

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Abstract

Trajectory tracking control is a key technology in the research and development of autonomous vehicles. In view of the fact that the traditional model predictive control (MPC) method does not consider the interaction of longitudinal and lateral forces in the trajectory tracking control of unmanned vehicle, a vehicle trajectory tracking control method based on model prediction is proposed. Considering the longitudinal and lateral coupling of tire force, a more accurate tire force model and dynamic model are obtained. Besides a variety of constraints such as control quantity, control increment and output are added. The co-simulation platform CarSim / Matlab / Simulink is used to verify the designed controller by taking the four-wheel front steering vehicle. The results show that the track tracking process is stable and reliable under the condition of double lane change and the tracking effect of vehicle to reference track is very ideal.

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APA

Liu, Z., & Kang, H. (2021). Research on trajectory tracking of unmanned vehicle based on model predictive control. In Journal of Physics: Conference Series (Vol. 1861). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/1861/1/012116

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