摘要
为解决高速列车运行过程中因轨面情况改变,导致列车没有达到最大黏着利用而出现空转或滑行等问题,设计了一种基于最大黏着系数的滑模自抗扰(SM-ADRC)黏着控制器;考虑轮轨间黏着特性的复杂、时变与非线性等特点,基于黏着机理分析,建立了轮轨间牵引系统的力学模型;采用极大似然估计(MLE)方法对不同轨面的相关参数进行辨识,计算了当前轨面的最大黏着系数,保证列车始终能达到最大黏着利用;通过引入滑模算法改进了自抗扰控制(ADRC)中非线性误差反馈控制律部分,设计了一种SM-ADRC黏着控制算法,利用Levant跟踪微分器减小初始跟踪误差,利用扩张状态观测器(ESO)估计和补偿系统总的外部扰动,由滑模控制提高系统的鲁棒性;采用MATLAB软件对CRH380A型高速列车进行仿真,在轨面情况改变时,由SM-ADRC黏着控制器控制列车跟踪设定速度,并将其与比例积分微分(PID)控制器、滑模控制器、ADRC的仿真结果进行对比。仿真结果表明:干燥轨面的最大黏着系数是0.160,16 s时辨识出真值;潮湿轨面的最大黏着系数是0.106,18 s时辨识出真值;ADRC的速度跟踪误差范围为±1 km·h^(-1),轨面变化后,速度跟踪误差波动幅度较大;SM-ADRC黏着控制器的速度跟踪误差范围为±0.4 km·h^(-1),轨面变化后,速度跟踪误差波动幅度较小,更加平滑稳定,速度控制跟踪精度更高,且优于PID和滑模控制方法。可见,所提出的SM-ADRC黏着控制器能够实现列车的快速黏着控制,并达到最大的黏着利用。
In order to solve the problems of idling or sliding due to the change of rail surface during the operation of high-speed train so that train did not reach the maximum adhesive utilization,a sliding mode active disturbance rejection controller(SM-ADRC)of adhesion based on the maximum adhesion coefficient was designed.Considering the complex,time-varying and nonlinear characteristics of wheel-rail adhesion,a mechanical model of wheel-rail traction system was established based on the analysis of adhesion mechanism.The maximum likelihood estimation(MLE)method was used to identify the relevant parameters of different rail surfaces,and the maximum adhesion coefficient of the current rail surface was calculated to ensure that the train could always achieve the maximum adhesion utilization.The nonlinear error feedback control law in the active disturbance rejection control(ADRC)was improved by introducing the sliding mode algorithm,a SM-ADRC algorithm of adhesion was designed,the Levant tracking differentiator was used to reduce the initial tracking error,and the extended state observer(ESO)was used to estimate and compensate the total external disturbance of the system.The robustness of the system was improved by the sliding mode control.The CRH380A high-speed train was simulated by the MATLAB software.When the rail surface condition changed,the SM-ADRC of adhesion controlled the train to track the set speed,and was compared with the proportional-integral-differential(PID)controller,sliding mode controller and ADRC in the simulation results.Simulation results show that the maximum adhesion coefficient of the dry rail surface is 0.160,and the true value is identified at 16 s.The maximum adhesion coefficient of the wet rail surface is 0.106,and the true value is identified at 18 s.The speed tracking error range of the ADRC is within±1 km·h~(-1),and the speed tracking error fluctuates greatly after the rail surface changes.The speed tracking error range of the SM-ADRC of adhesion is within±0.4 km·h~(-1).After the rail
作者
李中奇
黄琳静
周靓
杨辉
唐博伟
LI Zhong-qi;HUANG Lin-jing;ZHOU Liang;YANG Hui;TANG Bo-wei(School of Electrical and Automation Engineering,East China Jiaotong University,Nanchang 330013,Jiangxi,China;State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure,East China Jiaotong University,Nanchang 330013,Jiangxi,China)
出处
《交通运输工程学报》
EI
CSCD
北大核心
2023年第2期251-263,共13页
Journal of Traffic and Transportation Engineering
基金
国家重点研发计划(2020YFB1713703)
国家自然科学基金项目(52162048,61991404,U2034211)
江西省主要学科学术和技术带头人培养计划(20213BCJ22002)。
关键词
高速列车
黏着控制
自抗扰控制
滑模控制
轮轨模型
极大似然估计
high-speed train
adhesion control
active disturbance rejection control
sliding mode control
wheel-rail model
maximum likelihood estimation
