基于扰动补偿的高速列车自适应滑模黏着控制

Adaptive sliding mode adhesion control of high-speed train based on disturbance compensation

列车安全和平稳运行依赖于牵引力的有效发挥,而牵引力的有效发挥受限于轮轨间的黏着状态。为了解决高速列车行驶在低黏着轨面时牵引力不足的问题,考虑到车重、阻力、坡度等参数不易精确获取,设计一种基于扰动补偿的自适应滑模黏着控制算法。根据黏着计算模型和简化列车模型,建立高速列车轮轨动力学模型。通过设计动态观测精度更高的鲁棒黏着观测器,以精确获取当前轨面提供的黏着力。在此基础上,针对列车工作在最优黏着点附近时能够获得较大牵引力这一特性,采用梯度观测极值搜索算法获取该点附近的蠕滑速度。同时,设计基于扰动补偿的自适应滑模控制器控制电机输出转矩,使高速列车能够在部分系统参数未知的情况下跟踪极值搜索算法输出的蠕滑速度,从而提高列车牵引力。基于扰动补偿的自适应滑模控制,通过观测补偿系统不确定部分和自适应调节开关增益,减少滑模控制律抖振对黏着控制性能的影响。研究结果表明,基于扰动补偿的自适应滑模黏着控制算法在系统中存在未知参数时,能够控制列车在10 s内到达冰雪轨面最优黏着工作点附近,在1 s内到达潮湿轨面最优黏着工作点附近。此外,相比于传统滑模黏着控制和自适应滑模黏着控制,所提算法控制律抖振更低,并且能够更精确地搜寻和跟踪最优黏着工作点。所提算法可以为实际列车黏着控制算法设计提供参考。

The safe and stable operation of the train depends on the effective exertion of the traction force,which is limited by the adhesion state between the wheel and rail.To solve the problem of insufficient traction force of high-speed train running on low-adhesion rail surface,considering the difficulty in accurately obtaining parameters such as train weight,resistance,and slope,an adaptive sliding mode adhesion control algorithm based on disturbance compensation was designed.According to the adhesion calculation model and the simplified train model,the wheel-rail dynamic model of high-speed train was established.A robust adhesion observer with higher dynamic observation accuracy was designed to accurately obtain the adhesion force provided by the current rail surface.On this basis,aiming at the characteristic that the train can obtain large traction force when it works near the optimal adhesion point,the gradient observation extremum seeking algorithm was used to obtain the creep speed near the point.At the same time,an adaptive sliding mode controller based on disturbance compensation was designed to control the output torque of the motor.The high-speed train can track the creep speed output by the extremum seeking algorithm under the condition that some parameters of system are unknown,thereby improving the traction force.Adaptive sliding mode control based on disturbance compensation reduces the influence of control law chattering on the adhesion control performance by observing and compensating the uncertain part of the system and adaptively adjusting the switch gain.The results show that the adaptive sliding mode adhesion control algorithm based on disturbance compensation can control the train to reach the optimal adhesion working point of ice and snow rail surface within 10 s and reach the optimal adhesion working point of wet rail surface within 1 s when there are unknown parameters in the system.In addition,compared with the traditional sliding mode adhesion control and adaptive sliding model adhesion control,the proposed algorithm has lower control law chattering and can search and track the optimal adhesion working point more accurately.The proposed algorithm can provide a reference for the design of actual train adhesion control algorithm.