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作 者:周嘉俊 吴萌岭 刘宇康 田春 ZHOU Jiajun;WU Mengling;LIU Yukang;TIAN Chun(Institute of Rail Transit,Tongji University,Shanghai 201804,China)
机构地区:[1]同济大学铁道与城市轨道交通研究院,上海201804
出 处:《同济大学学报(自然科学版)》2020年第11期1657-1667,共11页Journal of Tongji University:Natural Science
基 金:国家自然科学基金(U1534205)。
摘 要:针对列车减速度控制中传统的比例、积分、微分控制(PID)及经典Smith预估方法控制效果不佳的问题,对Smith预估控制的反馈结构进行了改进,并从控制系统层面对影响列车实际减速度的不确定因素进行分类。建立列车制动单质点仿真模型,考察其在PID、Smith预估器以及改进Smith预估器控制下的系统阶跃响应特性。仿真结果表明,改进后的Smith算法具有良好的控制性能,且对参数变化具有更高的鲁棒性。最后在软件在环仿真平台的基础上,对比了非减速度控制、基于改进Smith预估算法的减速度控制、以及基于自适应参数估计算法的减速度控制的控制效果。结果表明,基于改进Smith预估算法的减速度控制不仅能实现目标减速度的精确跟踪,同时能够明显降低列车的纵向冲击。In view of the problem of the poor control in traditional proportion integration differentiation(PID)control and the classic Smith prediction method in train deceleration control,the feedback structure of Smith estimator was improved,and the uncertain factors that affect the actual deceleration of the train are classified from the perspective of control system.A single mass point simulation model for train braking was established,and its step response characteristics under the control of PID,Smith estimator and improved Smith estimator were analyzed.The simulation results show that the improved Smith estimator has a better control performance and a higher robustness.Finally,based on the software in the loop simulation,the control effects of non-deceleration control,deceleration control based on improved Smith estimator method,and deceleration control based on adaptive parameter estimation algorithm were compared.The results show that the deceleration control based on the improved Smith estimator can not only achieve accurate tracking of the target deceleration,but also significantly reduce the longitudinal impact of the train.
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