考虑复杂扰动的轻型商用车路径跟踪混合控制方法

doi:10.19562/j.chinasae.qcgc.2024.09.005

Abstract

Abstract:

Complex disturbances such as external interference， model uncertainty and parameter perturbation directly affect the accuracy and driving safety of intelligent vehicle path tracking control. Commercial vehicles are more susceptible to complex disturbances during driving because of their load characteristics. A hybrid path tracking control method is proposed in order to improve the accuracy and smoothness of commercial vehicle path tracking. Firstly， a robust sliding mode controller based on extended observer and an incremental LQR controller with stable changes are established. Particle swarm optimization algorithm is used to tune the parameters of the incremental LQR. Then， in order to improve robustness while weakening chattering， a fuzzy controller is used to adjust weight coefficient between them according to vehicle speed and lateral error. Finally， simulation analysis and vehicle experiments are conducted. The experimental data shows that SMC+LQR has good control performance to cope with complex external disturbances.

Key words: path tracking, complex disturbances, sliding mode control, extended state observer, incremental LQR, fuzzy algorithm

Jie Hu,Zhiling Zhang,Jiefeng Zhong,Wenlong Zhao,Jiachen Zheng,Silong Zhou,Zijun Qu. A Hybrid Control Strategy for Light Commercial Vehicle Path Tracking Considering Complex Disturbances[J].Automotive Engineering, 2024, 46(9): 1576-1586.

Figures/Tables 19

输入：粒子数n、迭代次数iter、变量范围（lowest， biggest）、

权重（ω， $c 1$ ， $c 2$ ）

输出：最优向量

$L 1$ = rand（lowest， biggest）， $V 1$ = rand（lowest， biggest）

$r 1$ = rand（0， 1）， $r 2$ = rand（0， 1）

for i = 1：iter

for j = 1：n

根据式（33）更新 $L j$ 和 $V j$

计算fitness（j）

end

now （i） = min（fitness）

global = min（ now ）

end

输出 global 的结果

参数	数值
质量m/kg	2 600
绕z轴转动惯量 $I z$ /（kg $?$ m²）	4 245
质心到前轴的距离a/m	1.35
质心到后轴的距离b/m	3.05
前轴总侧偏刚度 $k f$ /（N·rad^-1）	-173 000
后轴总侧偏刚度 $k r$ /（N·rad^-1）	-173 000

参数	数值
LQR矩阵 $Q, R$	$d i a g (3,0, 40,0, 8), 10$
LQR最大迭代步长	150
LQR衰减系数 $β$	0.1
SMC横向、航向误差权重 $t d, t φ$	$(1,0.1)$
SMC比例、微分项权重 $k p, k d$	$(2.2,0.2)$
SMC鲁棒性指标γ	0.5
状态观测器参数 $α 1, α 2, α 3$	（3，10，6）

参数	数值
质量m/kg	2 850
绕z轴转动惯量 $I z$ /（kg $?$ m²）	4 500
质心到前轴的距离a/m	1.20
质心到后轴的距离b/m	2.108
前轴总侧偏刚度 $k f /$ （N·rad^-1）	-170 000
后轴总侧偏刚度 $k r /$ （N·rad^-1）	-170 000
转向传动比	22

References 22

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\|e_d \|	v_x
\|e_d \|	S	M	B
S	VB	VB	B
M	VB	B	S
B	B	S	VS

项目	最大值	标准差
滑模横向误差/m	0.317	0.088
LQR横向误差/m	0.336	0.130
SMC+LQR横向误差/m	0.310	0.106
滑模航向误差/rad	-0.052	0.018
LQR航向误差/rad	-0.038	0.013
SMC+LQR航向误差/rad	-0.048	0.015

项目	最大值	标准差
滑模横向误差/m	0.432	0.146
LQR横向误差/m	0.646	0.206
SMC+LQR横向误差/m	0.218	0.064
滑模航向误差/rad	-0.095	0.024
LQR航向误差/rad	-0.116	0.027
SMC+LQR航向误差/rad	-0.089	0.017

项目	最大值	标准差
固定权重横向误差/m	0.460	0.152
可变权重横向误差/m	0.218	0.064
固定权重航向误差/rad	-0.110	0.018
可变权重航向误差/rad	-0.089	0.017

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A Hybrid Control Strategy for Light Commercial Vehicle Path Tracking Considering Complex Disturbances

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References 22

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