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Automotive Engineering ›› 2022, Vol. 44 ›› Issue (1): 8-16.doi: 10.19562/j.chinasae.qcgc.2022.01.002

Special Issue: 智能网联汽车技术专题-规划&控制2022年

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Longitudinal Cruise Control of Intelligent Vehicles Based on Adaptive Dynamic Sliding Mode Control

Jian Zhao,Jinpeng Du,Bing Zhu(),Zhiwei Wang,Zhicheng Chen,Xiaowen Tao   

  1. Jilin University,State Key Laboratory of Automotive Simulation and Control,Changchun  130022
  • Received:2021-08-23 Revised:2021-09-28 Online:2022-01-25 Published:2022-01-21
  • Contact: Bing Zhu E-mail:zhubing@jlu.edu.cn

Abstract:

To eliminate the effects of parameter uncertainty and external disturbances on the longitudinal cruise control of intelligent vehicles, a longitudinal cruise control method based on adaptive dynamic sliding mode is proposed. The vehicle longitudinal dynamics model is established with the derivative term of generalized longitudinal force as control input, and a novel sliding mode function is constructed based on the backsteping method to ensure that the vehicle speed and longitudinal acceleration converge to the desired value at the same time. On this basis, the dynamic sliding mode control law of the desired generalized longitudinal force is designed and the unknown disturbances in the control law are compensated adaptively by using RBF neural network. The actuator selection module is designed to convert the desired generalized longitudinal force into the desired control input in actuator layer, with the comparative simulation and real vehicle test conducted. The results show that the longitudinal cruise control method proposed for intelligent vehicles can effectively eliminate the influences of parameter uncertainty and external disturbance, improve the chattering of traditional sliding mode control, and achieve the stable and accurate tracking of the desired cruise speed.

Key words: cruise control, dynamic sliding mode control, adaptive control, backstepping method, RBF neural network