The invention discloses a train speed tracking control method based on an equivalent sliding mode and an RBF (Radial Basis Function) neural network, belongs to the technical field of train speed tracking, and provides a neural network equivalent sliding mode controller for a control target based on strong nonlinear interference in a train running process so as to enhance the robustness of a control system. Sliding mode control is introduced, and the effectiveness of the algorithm is verified through simulation; in order to suppress an inherent buffeting phenomenon of sliding mode control in a convergence process, a rule base is established by combining excellent driver driving experience on the basis of a sliding mode control algorithm framework, a neural network trainer is established, and a switching gain obtained through training effectively softens a discontinuous switching phenomenon so as to weaken buffeting, so that the stability of the sliding mode control algorithm is improved. According to the invention, the anti-disturbance capability and the control precision of the system are enhanced, it can be ensured that the train accurately tracks the reference trajectory during operation, control input is smoothed, the chattering phenomenon is weakened, and frequent switching and overshoot of working condition switching points are avoided.

    本发明公开了一种基于等效滑模及RBF神经网络的列车速度跟踪控制方法,属于列车速度跟踪技术领域,本发明基于列车运行过程中的所受到的强非线性干扰,针对控制目标提出了神经网络等效滑模控制器,以增强控制系统鲁棒性为目的,引入滑模控制,并通过仿真验证了算法的有效性;为抑制滑模控制在收敛过程中固有的抖振现象,在滑模控制算法框架的基础上结合优秀司机驾驶经验建立规则库,并建立神经网络训练器,经训练得到的切换增益有效地柔化不连续开关现象从而削弱了抖振,增强了系统的抗扰动能力和控制精度,本发明可以保证列车运行时精确地跟踪参考轨迹,同时平滑了控制输入,削弱了抖振现象,避免频繁切换以及工况切换点的超调现象。


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    Titel :

    Train speed tracking control method based on equivalent sliding mode and RBF neural network


    Weitere Titelangaben:

    一种基于等效滑模及RBF神经网络的列车速度跟踪控制方法


    Beteiligte:
    LIANG HUADIAN (Autor:in) / LEI YU (Autor:in) / SONG DEJIAN (Autor:in) / LIN YE (Autor:in) / WANG YONG (Autor:in) / HUANG PAN (Autor:in) / TANG LIANQIAO (Autor:in) / LU YUHAO (Autor:in)

    Erscheinungsdatum :

    12.05.2023


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    B61L Leiten des Eisenbahnverkehrs , GUIDING RAILWAY TRAFFIC / G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL



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