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Multimode Intelligent Control Based on Multidata Fusion Filtering in High-Speed Train Traffic Signal and Control
Journal of Sensors ( IF 1.9 ) Pub Date : 2021-06-01 , DOI: 10.1155/2021/6081999 Bin Huang 1 , Ying Huang 1
Journal of Sensors ( IF 1.9 ) Pub Date : 2021-06-01 , DOI: 10.1155/2021/6081999 Bin Huang 1 , Ying Huang 1
Affiliation
As the speed of high-speed trains continues to increase, the intelligent monitoring of high-speed trains has become a concern of people. This research mainly discusses the application of multimode intelligent control of multidata fusion filtering in high-speed train traffic signal and control. In multimodal intelligent control, BangBang, PI control, adaptive fuzzy PID control, and expert monitoring control under special circumstances can be used, respectively, according to the error and the rate of change of the error, which can achieve the best control effect under safe conditions. Take the allowable speed of ATP as the target speed of the control system, and combine the operation process, operation requirements, traction characteristics, braking characteristics of high-speed trains, and meet the two conditions for improving the operating efficiency of high-speed trains. According to the dynamic expected speed value of high-speed trains, dynamically adjust the switching threshold. This study uses a pulse signal generator to simulate the speed data of the vehicle speed sensor (all pulse data), and then read the speed (pulse) signal data through the pulse signal acquisition card, and display the simulated speed data under the Kingview software. The monitoring computer is used to collect train speed information, display speed information, manage speed information, and output speed information. Then, through OPC technology, the simulation speed data is transmitted to MATLAB software for multidata fusion filtering processing and multimodal control simulation. In the simulation process, the train adopts a multimodal intelligent control response scheme, with a total time of 2183.7 s, which is shortened by 214.5 s and improved by nearly 10%. The multimode intelligent control scheme of multidata fusion filtering proposed in this study can better meet the control of high-speed train traffic signals.
中文翻译:
高速列车交通信号与控制中基于多数据融合滤波的多模智能控制
随着高铁运行速度的不断提高,高铁智能监控成为人们关注的问题。本研究主要探讨多数据融合滤波多模智能控制在高速列车交通信号与控制中的应用。在多模态智能控制中,可根据误差和误差变化率分别采用棒棒、PI控制、自适应模糊PID控制和专家监控控制,在安全的情况下达到最佳控制效果。使适应。以ATP的允许速度作为控制系统的目标速度,结合高速列车的运行过程、运行要求、牵引特性、制动特性,并满足提高高速列车运行效率的两个条件。根据高速列车动态预期速度值,动态调整切换阈值。本研究采用脉冲信号发生器模拟车速传感器的速度数据(均为脉冲数据),然后通过脉冲信号采集卡读取速度(脉冲)信号数据,并在组态王软件下显示模拟的速度数据. 监控计算机用于采集列车速度信息、显示速度信息、管理速度信息、输出速度信息。然后通过OPC技术将仿真速度数据传输到MATLAB软件进行多数据融合滤波处理和多模态控制仿真。在模拟过程中,列车采用多模态智能控制响应方案,总时间2183.7s,缩短214.5s,提高近10%。本研究提出的多数据融合滤波多模智能控制方案可以更好地满足高速列车交通信号的控制。
更新日期:2021-06-01
中文翻译:
高速列车交通信号与控制中基于多数据融合滤波的多模智能控制
随着高铁运行速度的不断提高,高铁智能监控成为人们关注的问题。本研究主要探讨多数据融合滤波多模智能控制在高速列车交通信号与控制中的应用。在多模态智能控制中,可根据误差和误差变化率分别采用棒棒、PI控制、自适应模糊PID控制和专家监控控制,在安全的情况下达到最佳控制效果。使适应。以ATP的允许速度作为控制系统的目标速度,结合高速列车的运行过程、运行要求、牵引特性、制动特性,并满足提高高速列车运行效率的两个条件。根据高速列车动态预期速度值,动态调整切换阈值。本研究采用脉冲信号发生器模拟车速传感器的速度数据(均为脉冲数据),然后通过脉冲信号采集卡读取速度(脉冲)信号数据,并在组态王软件下显示模拟的速度数据. 监控计算机用于采集列车速度信息、显示速度信息、管理速度信息、输出速度信息。然后通过OPC技术将仿真速度数据传输到MATLAB软件进行多数据融合滤波处理和多模态控制仿真。在模拟过程中,列车采用多模态智能控制响应方案,总时间2183.7s,缩短214.5s,提高近10%。本研究提出的多数据融合滤波多模智能控制方案可以更好地满足高速列车交通信号的控制。