基于Smith预估器的模糊PID调车自动驾驶系统速度控制研究

Research on Speed Control of Fuzzy PID Shunting ATO System Based on Smith Predictor

针对铁路站场调车作业的复杂性,研发基于调车的自动驾驶系统可降低劳动强度并提高车站作业效率,而速度控制策略是系统的重点和难点。根据调车牵引控制系统和制动控制系统特性,建立传递函数模型,并对模型参数的不稳定因素进行分析;利用Smith预估方法处理时滞系统的优势,结合模糊PID算法,设计基于Smith预估器的模糊PID控制器(简称新型控制器);通过模拟模型参数不稳定,分别使用阶跃响应曲线和司机实操速度曲线进行仿真,对比传统的PID控制器、模糊PID控制器与新型控制器的控制效果。结果表明:新型控制器适应能力更强,速度跟踪效果和停车精度都更高。

To address the complexities of shunting operations in railway stations and yards,the research and development of a shunting-based automatic train operation(ATO)system can help effectively reduce labor intensity and enhance the efficiency of station operations.The speed control strategy represents a key and difficult aspect of the system.A transfer function model is developed and unstable factors within the model parameters are analyzed according to the characteristics of the shunting traction control system and braking control system.Utilizing the advantages of Smith prediction in handling time-delay systems and incorporating a fuzzy PID algorithm,a fuzzy PID controller based on the Smith predictor(referred to as the“new controller”)is designed.Through the simulation of instability of model parameters,step response curves and the driver’s practical operation speed curves are used for the simulation to compare the control effects of the conventional PID controller,the fuzzy PID controller,and the new controller.The results indicate that the new controller exhibits superior adaptability and provides better speed tracking performance and stop precision.