Lateral control using LQR for intelligent vehicles based on the optimal front-tire lateral force

CHEN Liang; QIN Zhaobo; KONG Weiwei; CHEN Xin

doi:10.16511/j.cnki.qhdxxb.2020.22.028

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Journal of Tsinghua University(Science and Technology) ›› 2021, Vol. 61 ›› Issue (9) : 906-912. DOI: 10.16511/j.cnki.qhdxxb.2020.22.028

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Lateral control using LQR for intelligent vehicles based on the optimal front-tire lateral force

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Abstract

A lateral control method for intelligent vehicles is developed based on the optimal front-tire lateral force to improve the lateral stability and the path tracking accuracy of intelligent vehicles going around large curvature turns. A linear quadratic regulator (LQR) controller using feedforward and feedback control is used to determine the desired front-tire lateral force in real time to reduce the tracking error. The control input is then converted into the desired steering angle based on the brush tire model. This method properly retains the nonlinear characteristics of the vehicle and tire models. The LQR controller is verified via simulations on PreScan. The results show that this LQR controller not only reduces the path tracking error relative to the general LQR method, but also ensures lateral stability of the vehicle.

Key words

intelligent vehicle / path tracking control / vehicle lateral stability / linear quadratic regulator (LQR)

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CHEN Liang, QIN Zhaobo, KONG Weiwei, CHEN Xin. Lateral control using LQR for intelligent vehicles based on the optimal front-tire lateral force[J]. Journal of Tsinghua University(Science and Technology). 2021, 61(9): 906-912 https://doi.org/10.16511/j.cnki.qhdxxb.2020.22.028

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