Abstract: This paper focuses on the speed control of high-speed train (HST) automatic operation system under actuator fault and speed limitation, and proposes a Finite-Iteration Constrained Adaptive Iterative Learning Fault-Tolerant Control (FI-CAILFTC) method. Based on the Barrier Composite Energy Function (BCEF), this paper defines the convergence conditions for a finite number of operations along the iterative domain, and calculates the required number of operations using the desired arbitrary tracking accuracy. The method then improves the controller parameter selection to ensure finite number of operation convergence. The iterative learning control algorithms are designed with adaptive fault tolerance for adaptive estimation and compensation of unknown time-varying and iteration-varying actuator faults. To address the overspeed issue of the HST operation, this study added an overspeed protection mechanism to ensure that the actual operation speed of the HST always meets the speed constraints and to ensure the safe operation of the train. The China Railway High-speed (CRH)-3 high-speed locomotive train is used as an example for the simulation analysis. The results show that the HST speed tracking error under the FI-CAILFTC method reaches the desired control accuracy of 0.2 after the pre-calculated 17th iteration, compared with the comparison algorithms, the control accuracy was improved by 90.70% and 90.22%, respectively. The FI-CAILFTC has faster convergence and better adaptive fault tolerance. The actual operation speed of the HST is always active to satisfy the speed constraints.

Key words: railway transportation, finite-iteration convergence, adaptive iterative learning fault-tolerant control, high-speed train, over-speed protection, actuator faults

摘要： 为研究高速列车(High-Speed Train, HST)自动运行系统在执行器故障和速度受限下的速度控制问题，本文提出一种有限次运行收敛的受限自适应迭代学习容错控制 (Finite- Iteration Constrained Adaptive Iterative Learning Fault-Tolerant Control, FI-CAILFTC)方法。首先，基于障碍组合能量函数(Barrier Composite Energy Function, BCEF)构建沿迭代域方向有限次运行收敛条件，并且利用所期望任意跟踪精度计算所需运行次数，同时，指导控制器参数选择，以保证HST有限次运行收敛性；其次，设计具有自适应容错能力的迭代学习控制算法，对未知时变且迭代变化的执行器故障进行自适应估计和补偿；再次，针对HST运行过程中超速问题，在所设计容错控制器基础上，加入超速防护机制，保证HST实际运行速度始终满足速度约束，保障列车安全运行；最后，以CRH-3型高速动车组列车作为研究对象，对设计的控制方法进行仿真研究。仿真结果表明：FI-CAILFTC 方法下，HST 速度跟踪误差在预先计算出的第 17 次迭代后达到期望控制精度0.2，相较于对比算法，控制精度分别提高了90.70%和90.22%；FI-CAILFTC有更快的收敛速度和更好的自适应容错能力；HST实际运行速度始终主动满足速度受限。

关键词: 铁路运输, 有限次运行收敛, 自适应迭代学习容错控制, 高速列车, 超速防护, 执行器 故障