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Model-based verification method for solving the parameter uncertainty in the train control system

机译:解决列车控制系统参数不确定性的基于模型的验证方法

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This paper presents a parameter analysis method to solve the parameter uncertainty problem for hybrid system and explore the correlation of key parameters for distributed control system. For improving the reusability of control model, the proposed approach provides the support for obtaining the constraint sets of all uncertain parameters in the abstract linear hybrid automata (LHA) model when satisfying the safety requirements of the train control system. Then, in order to solve the state space explosion problem, the online verification method is proposed to monitor the operating status of high-speed trains online because of the real-time property of the train control system. Furthermore, we construct the LHA formal models of train tracking model and movement authority (MA) generation process as cases to illustrate the effectiveness and efficiency of the proposed method. In the first case, we obtain the constraint sets of uncertain parameters to avoid collision between trains. In the second case, the correlation of position report cycle and MA generation cycle is analyzed under both the normal and the abnormal condition influenced by packet-loss factor. Finally, considering stochastic characterization of time distributions and real-time feature of moving block control system, the transient probabilities of wireless communication process are obtained by stochastic time petri nets. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文提出了一种参数分析方法,用于解决混合系统参数不确定性问题,并探索分布式控制系统关键参数的相关性。为了提高控制模型的可重用性,该方法为满足列车控制系统的安全性要求提供了抽象线性混合自动机(LHA)模型中所有不确定参数约束集的支持。然后,为解决状态空间爆炸问题,鉴于列车控制系统的实时性,提出了一种在线验证方法来在线监测高速列车的运行状态。此外,我们构建了LHA形式的火车跟踪模型和运动授权(MA)生成过程的正式模型,以说明该方法的有效性和效率。在第一种情况下,我们获得不确定参数的约束集,以避免列车之间发生碰撞。在第二种情况下,分析了正常状态和异常状态下丢包率影响下位置报告周期与MA生成周期的相关性。最后,考虑时间分布的随机性和运动块控制系统的实时性,通过随机时间Petri网获得无线通信过程的暂态概率。 (C)2015 Elsevier Ltd.保留所有权利。

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