高速列车纵向动力学建模与自适应RBFNN控制

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中文摘要：高速列车由多节车厢链接而成的结构特性导致其高速运行在变路况线路条件下难以有效地对其进行优化控制.针对上述问题,提出一种高速列车纵向动力学模型与径向基函数神经网络(RBFNN)控制策略.考虑列车车钩力和复杂线路条件,分析整列车前后的不同受力情况,建立列车纵向动力学模型.针对该模型无外加干扰时设计一种理想反馈控制律,引入RBFNN对理想控制输出进行拟合,在考虑干扰项影响的情况下,通过设计参数估计自适应律代替神经网络权值的调整,并对其进行Lyapunov稳定性证明.采用京石武高铁北京西—郑州东段的CRH380B型高速列车真实线路运行数据进行仿真模拟,并在相同条件下与反演滑模(BSSM)控制器的仿真结果进行对比.仿真结果表明所提控制器更能有效应对复杂路况变化和外界干扰,对高速列车具有更好的控制效果,改善其运行的平稳性及高效性.

外文标题：Longitudinal Dynamics Modeling and Adaptive RBFNN Control for High-speed Trains

外文摘要：Due to the structural characteristics of high-speed trains linked by multiple carriages,it is difficult to effec-tively control the high-speed trains during high speed operation under changing high-speed railway line conditions.In re-sponse to the above problems,this paper proposed a high-speed train longitudinal dynamics model and an adaptive radial basis function neural network(RBFNN)control strategy.Firstly,considering the train coupler force and complex line conditions,based on the analysis of the different forces in the front and rear of the whole train,the train longitudinal dy-namics model was established.Secondly,an ideal feedback control law was designed for the model without external inter-ferences,and RBFNN was introduced to fit the ideal control output.Then,the adaptive law of design parameter estima-tion was used to replace the adjustment of the weights of the neural network under the condition of considering the influ-ence of the interference term,and the Lyapunov stability of the model was proved.Finally,the real line running data of the CRH380B high-speed train from the section between the Beijingxi Railway Station and Zhengzhoudong Railway Sta-tion was used for simulation,and the simulation results were compared with the backstepping sliding mode(BSSM)con-troller under the same conditions.The simulation results show that the proposed controller can more effectively deal with complex high-speed railway condition changes and external disturbances,has better control effect on high-speed trains,and improves the stability and efficiency of their operation.

外文关键词：

high-speed trainlongitudinal dynamics modelradial basis function neural networkadaptive algorithmLya-punov theory

作者：

付雅婷、胡东亮、杨辉、欧阳超明

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作者单位：

华东交通大学电气与自动化工程学院,江西南昌 330013

华东交通大学轨道交通基础设施性能检测与保障国家重点实验室,江西南昌 330013

中国铁路广州局集团有限公司,湖南长沙 410001

关键词：

高速列车纵向动力学模型径向基函数神经网络自适应算法 Lyapunov理论

基金：

国家自然科学基金国家自然科学基金国家自然科学基金江西省技术创新引导类计划流程工业综合自动化国家重点实验室联合基金

项目编号：

62363011U20342115216204820203AE10092022-KF-21-03

出版年：

2024

DOI：

10.3969/j.issn.1001-8360.2024.01.005

铁道学报

中国铁道学会

铁道学报

CSTPCD北大核心

影响因子：0.9

ISSN：1001-8360

年,卷(期)：2024.46(1)

参考文献量31