基于改进大脑情感学习模型的车辆纵向跟随

doi:10.13229/j.cnki.jdxbgxb20210546

Abstract

Abstract:

In order to improve the safety of longitudinal follow-up control algorithm for unmanned vehicles， an indirect adaptive brain emotion neural robust controller （iARBERC） was proposed based on the brain emotion learning model and the good nonlinear approximation characteristics of radial basis function neural network. The stability of the control system was proved by Lyapunov analysis method. The simulation results show that iARBERC has the fastest response speed， the smallest tracking error and the best robust performance. Although the total control energy was improved， the deviation is less than 4%. Finally， iARBERC was applied to the semi-physical simulation platform of the following control system of the unmanned vehicle. The results show that the vehicle equipped with iARBERC has good following ability to the frequently changing longitudinal speed.

Key words: unmanned driving, longitudinal following, brain emotional learning, nonlinear approximation, robustness, semi-physical simulation

CLC Number:

U461.9

Min-xiang WEI,Jia-wei YANG,Kai CHEN,Zhi-hao WANG,Zhao SHA. Vehicle longitudinal following based on improved brain emotional learning model[J].Journal of Jilin University(Engineering and Technology Edition), 2022, 52(12): 2994-3005.

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类别		计算时间
类别		RBFNN	ARBENC（2018）	iARBERC
无干扰	max	0.0064	0.0072	0.0032
	min	3.8860×10^-4	4.0770×10^-4	4.4670×10^-4
	mean	7.6982×10^-4	7.5332×10^-4	7.1550×10^-4
正旋干扰	max	0.0064	0.0066	0.0040
	min	4.0020×10^-4	3.9870×10^-4	3.8680×10^-4
	mean	7.8781×10^-4	7.5654×10^-4	7.6305×10^-4
脉冲干扰	max	0.0103	0.0120	0.0104
	min	0.0027	0.0026	0.0024
	mean	0.0081	0.0099	0.0070
测量误差SNR=35	max	0.0442	0.0115	0.0287
	min	3.7831×10^-4	3.5920×10^-4	3.8900×10^-4
	mean	0.0011	0.0011	9.2810×10^-4

类别		MSE
类别		RBFNN	ARBENC（2018）	iARBERC
无干扰		0.001 042 374	0.001 090 652	0.000 995 991
正旋干扰		0.001 048 259	0.001 099 018	0.001 004 257
脉冲干扰		0.001 045 110	0.001 094 535	0.000 996 313
测量误差 SNR=35	mean	0.001 043 353	0.001 090 535	0.000 996 040
	max	0.001 051 434	0.001 092 145	0.001 006 870
	min	0.001 035 645	0.001 088 323	0.000 990 060

类别		J
类别		RBFNN	ARBENC（2018）	iARBERC
无干扰		11.448 6	11.295 8	11.648 9
正旋干扰		12.146 2	11.955 5	12.375 1
脉冲干扰		13.501 1	13.352 4	13.676 9
测量误差 SNR=35	mean	14.199 9	12.290 1	14.599 34
	max	14.480 1	12.471 2	14.958 85
	min	13.861 68	12.085 1	14.385 2

Vehicle longitudinal following based on improved brain emotional learning model

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