重载机车无模型黏着预测控制研究  

Model-free adhesion predictive control of heavy-haul locomotive

作　　者：程翔 何静[2] 张昌凡[2] 贾林[2] CHENG Xiang;HE Jing;ZHANG Changfan;JIA Lin(School of Artificial Intelligence,Hunan Railway Professional College,Zhuzhou 412007,China;School of Rail Transit,Hunan University of Technology,Zhuzhou 412001,China)

机构地区：[1]湖南铁道职业技术学院人工智能学院,湖南株洲412007 [2]湖南工业大学轨道交通学院,湖南株洲412001

出　　处：《铁道科学与工程学报》2024年第9期3765-3774,共10页Journal of Railway Science and Engineering

基　　金：国家自然科学基金资助项目(61273137,62303178);湖南省自然科学基金资助项目(2023JJ60232);湖南省教育厅科研资助项目(23B1018,22B0577)。

摘　　要：重载机车牵引动力的有效发挥依赖于轮对和钢轨接触时形成的黏着力,然而,由于重载机车黏着过程动力学非线性强、变量耦合多、最优蠕滑速度检测难,导致传统控制方法难以对黏着进行高效控制。针对该问题,提出一种无模型黏着集成预测控制方法。首先,分析传统无模型方法存在的问题,建立重载机车蠕滑速度新型扩张超局部模型。其次,设计扩展滑模观测器估计超局部模型中的不确定部分,不同于传统观测方法,该观测器能够“一步式”估算机车当前的黏着系数和蠕滑速度;同时引入一种改进的后调制无稳态振荡极值搜索方法并进行收敛性分析,在有效黏着系数观测的基础上实时寻优期望蠕滑速度。再次,基于最优蠕滑速度极值搜索设计一种离散蠕滑速度预测控制器,避免传统的控制律设计中引入蠕滑速度微分导致的噪声放大问题,并证明闭环控制下的系统稳定性。最后,与传统滑模黏着控制策略进行仿真对比,印证本文所提控制框架能有效降低黏着控制策略设计的复杂度,提升控制转矩的平滑度。在轨面条件突变的情况下,改进无稳态极值搜索方法能够准确搜索适合的最优蠕滑速度,在3种预设工况下都能够准确锁定最优值;离散黏着控制律能够更为精确地控制驱动转矩,与传统的带有蠕滑速度微分的黏着控制律相比极大地降低了转矩抖振。由此可知,该重载机车无模型黏着预测控制方法能够充分发挥黏着系统效能,实现多工况瞬变下的高效黏着控制。The effective traction of heavy-haul locomotives is contingent on adhesion forces generated at the wheel-rail interface.Traditional control methods struggle with efficient adhesion control due to the nonlinear dynamics,variable coupling,and difficulty in detecting the optimal creep speed in the adhesion process of these locomotives.To address this issue,a model-free integrated predictive control approach for adhesion was proposed.Initially,issues with traditional model-free methods were analyzed,and a novel expanded ultra-local model for locomotive creep speed was established.An extended sliding mode observer was designed to estimate the uncertain components of the ultra-local model,which uniquely estimated the current adhesion coefficient and creep speed in a“one-step”manner,differing from traditional observation methods.An improved post-modulated,oscillation-free extremum seeking method with convergence analysis was introduced to optimize the desired creep speed in real-time,based on effective adhesion coefficient observation.Subsequently,a discrete creep speed predictive controller was designed based on the extremum seeking of the optimal creep speed,mitigating noise amplification issues associated with differential speed in traditional control law designs and proving system stability under closed-loop control.Results are drawn as follows.Simulations can demonstrate the proposed control framework’s effectiveness in reducing complexity in adhesion control strategy design and enhancing the smoothness of control torque.The improved extremum seeking method precisely identifies optimal creep speeds under sudden track conditions changes and locks in the optimum across various predefined scenarios.The proposed discrete adhesion control law accurately modulates the drive torque,significantly reducing torque jitter compared to traditional control laws incorporating creep speed differentials.The model-free adhesion predictive control method can effectively optimize adhesion system performance,and achieve efficient

关 键 词：重载机车 黏着控制 无模型控制 极值搜索 扩张观测器 

分 类 号：U2[交通运输工程—道路与铁道工程]