高速铁路列车动力学系统稳定性能控制研究

摘要

高速铁路具有速度高、能耗低、运力大、安全正点等诸多技术经济优势,因此成为世界各国优先发展的和谐友好绿色交通工具.然而,随着列车运行速度的提高,列车与接触网、轮轨、空气的相互作用显著加剧,列车系统的动态作用环境明显恶化,这给高速列车的安全、稳定运行带来巨大隐患.因此,为了保障高速列车的安全运行、促进高速铁路的健康可持续发展,迫切需要开展适合于高速列车的有效建模、控制、优化的基础研究.基于高速列车动力学模型的建立,对高速列车动力学模型进行数学化简,进而运用极大似然辨识方法和闭环频域辨识方法对高速列车动力学模型进行了辨识.通过两种不同辨识方法的比较可以了解模型中参数对模型影响的程度,可以为准确建模提供理论基础.首先,构建了描述高速列车单质点力学行为的随机离散非线性状态空间方程和差分方程;其次,用辨识算法进行仿真,分析算法的收敛速度和参数的影响程度;最后,通过设计控制器控制的优劣来评价辨识方法的有效性.结果表明,所提出的辨识方法是有效性的.%High-speed railway with high speed,low energy consumption,capacity,safety punctuation and many other technical and economic advantages,thus becoming the world's priority development of harmonious and friendly green transport.However,with the increase of train running speed,the interaction between train and catenary,wheel / rail and air is obviously exacerbated,and the dynamic environment of train system is obviously deteriorated,which brings great risks to the safe and stable operation of high-speed train.Therefore,in order to ensure the safe operation of high-speed trains and promote the healthy and sustainable development of high-speed railway,it is urgent to carry out basic research on effective modeling,control and optimization suitable for high-speed trains.Based on the establishment of the dynamic model of high-speed train,the dynamic model of high-speed train is simulated,and the dynamic model of high-speed train is identified by maximum likelihood identification method and closed-loop frequency domain identification method.The degree of influence of the parameters on the model can be understood by comparing the two different identification methods,which can provide the theoretical basis for accurate modeling.Firstly,the stochastic discrete nonlinear state space equation and the difference equation describing the mechanical behavior of the high-speed trains are constructed.Secondly,the convergence speed and the influence degree of the parameters are analyzed by the identification algorithm.Finally,To evaluate the effectiveness of the identification method.The results show that the proposed identification method is effective.