Robust Lateral Control of Intelligent Vehicle in the Human-machine Sharing Based on μ-synthesis

doi:10.3901/JME.2020.04.104

Abstract

Abstract: In most intelligent vehicle lateral control studies, there is a shortcoming that the influence of driver's misoperation is not taken into account. The human-machine sharing control problem is taken as the research object. The driver steering torque and vehicle state are considered as inputs of the controller. Firstly, the steering system and 2-DOF vehicle model is established, and in the vehicle local coordinate system, a virtual path planning is realized according to the curvature information of the preview point. And an upper desired yaw rate controller is designed based on vehicle statue and the desired lane. Secondly, a lower μ-synthesis robust controller considering vehicle parameter uncertainty and sensor noise is designed to make vehicle tracking the desired yaw rate and the desired lateral position, ensure vehicle tracking the target path stably, in which crosswind and driver's misoperation are considered as disturbance input, and yaw rate, steering angle, steering torque and desired yaw rate are considered as feedback variables. Finally, lane changing and lane keeping simulation is carried out, and the HIL test is implemented on the HIL test bench based on CarSim/LabVIEW, the simulation and test results show that the proposed lateral control algorithm not only assist driver to control vehicle tracking desired lane more accurately but also can restrain the crosswind and prevent driver's misoperation.

Key words: intelligent vehicle, lateral control, human-machine sharing, μ integrated control

CLC Number:

TG156

XIE Youhao, WEI Zhenya, ZHAO Linfeng, WANG Jiaen, CHEN Wuwei. Robust Lateral Control of Intelligent Vehicle in the Human-machine Sharing Based on μ-synthesis[J]. Journal of Mechanical Engineering, 2020, 56(4): 104-114.

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