驾驶机器人转向操纵的动态模型预测控制方法

doi:10.16183/j.cnki.jsjtu.2021.108

摘要/Abstract

摘要：

为实现驾驶机器人对试验车辆进行精确的转向操纵,提出了一种驾驶机器人转向操纵的动态模型预测控制方法.建立了驾驶机器人与被操纵车辆的耦合动力学模型,并对耦合模型的可控性进行判别.利用卡尔曼滤波器对耦合模型进行状态估计,并结合估计状态设计了模型预测控制器.将最小二乘法用于路径曲率与预测时域的非线性关系的拟合,设计了具有可变预测时域的动态模型预测控制器.进行了不同驾驶工况下的驾驶机器人转向操纵仿真与试验,研究结果表明了所提方法的有效性.

关键词: 驾驶机器人, 转向操纵, 卡尔曼滤波器, 预测时域, 动态模型预测控制

Abstract:

A dynamic model predictive control method for driving robots is proposed to realize accurate steering control of the test vehicle. First, the coupling dynamics model of the driving robot and the controlled vehicle is established, and the controllability of the coupling model is judged. Then, the Kalman filter is used to estimate the state of the coupled model, and a model predictive controller is designed according to the estimated state. The least square method is adapted to fit the nonlinear relationship between path curvature and prediction horizon, and a dynamic model predictive controller with variable prediction horizon is designed. Finally, the simulation and the test of the steering control of the driving robot at different conditions are conducted, and the results verify the effectiveness of the proposed method.

Key words: driving robot, steering control, Kalman filter, prediction horizon, dynamic model predictive control

中图分类号:

TH113
U467.1

姜俊豪, 陈刚. 驾驶机器人转向操纵的动态模型预测控制方法[J]. 上海交通大学学报, 2022, 56(5): 594-603.

JIANG Junhao, CHEN Gang. Dynamic Model Predictive Control Method for Steering Control of Driving Robot[J]. Journal of Shanghai Jiao Tong University, 2022, 56(5): 594-603.

图/表 14

图1

图2

图3

图4

图5

表1

时域数据

ρ/m^-1	$N p *$	ρ/m^-1	$N p *$
0	8	0.14	12
0.02	9	0.16	13
0.04	10	0.18	14
0.06	10	0.20	15
0.08	11	0.22	17
0.10	11	0.24	18
0.12	12

表1

表2

表3

图6

图7

表4

关键参数

对象	参数	数值	对象	参数	数值
驾驶机器人	L/H	0.012	驾驶机器人	μ/(N·m·rpm^-1)	0.05
	k_t/(N·m·A^-1)	0.47		R/Ω	0.42
	k_e/[V·(rad·s)^-1]	0.0172		i₀	15
被操纵车辆	m/kg	1126	被操纵车辆	K₀/(N·m·rad^-1)	6000
	l_f/m	1.014		J_e/(kg·m²)	14
	l_r/m	1.534		e/m	0.0035
	K_f/(N·rad^-1)	51480		J_z/(kg·m²)	2697
	K_r/(N·rad^-1)	87416		i_e	20
控制器	ΔU_max/V	3	控制器	N_pmin	8
	ΔU_min/V	-3		$w q i$	20000
	U_max/V	24		$w r j$	0.1
	U_min/V	-24		N_c	10
	N_pmax	19

表4

图8

表5

图9

参考文献 19

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参数	最终值	95%置信区间
b₀	0.1016	(0.07692, 0.1264)
b₁	0.1089	(0.09469, 0.1231)

评价指标	取值
均方根误差	0.44
确定系数	0.98
自由度调整确定系数	0.97

工况	k_p	k_i
不考虑踏板特性	160.5	424.9
考虑踏板特性	193.9	465.9