The invention relates to an uncertain vehicle following system robust optimal control method based on data driving, and the method comprises the steps: firstly, building a longitudinal dynamic model and a tracking error dynamic model of a vehicle for an intelligent vehicle with matching disturbance and uncertain parameters; and then, designing a self-adaptive optimal controller to realize robust control of the uncertain system. Wherein the recurrent neural network is introduced to adaptively estimate the dynamic characteristics of the system, and adaptive dynamic programming is adopted to approximate an unknown optimal cost function in the control law. The method provided by the invention has good performance for a system with uncertainty and unknown matching interference, provides a new thought and method for adaptive control in practical application, and also provides a new solution thought for the control problem of an uncertain system.

    本发明涉及一种基于数据驱动的不确定跟车系统鲁棒最优控制方法,基于数据驱动的不确定跟车系统鲁棒最优控制方法,首先,针对存在匹配扰动和不确定参数的智能车辆,建立车辆的纵向动力学模型和跟踪误差动力学模型。接着,设计了一个自适应最优控制器来实现不确定系统的鲁棒控制。其中,引入循环神经网络来自适应地估计系统的动态特性,并采用自适应动态规划来近似控制律中未知的最优成本函数。本发明所提出的方法针对具有不确定性和未知匹配干扰的系统具有良好的性能,为实际应用中的自适应控制提供了新的思路和方法,同时也对不确定系统的控制问题提供了一种新的解决思路。


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    Titel :

    Robust optimal control method for uncertain car following system based on data driving


    Weitere Titelangaben:

    一种基于数据驱动的不确定跟车系统鲁棒最优控制方法


    Beteiligte:
    ZHAI CHUNJIE (Autor:in) / ZHAN YIXIAO (Autor:in) / KIM BIN-HO (Autor:in) / YIN KE (Autor:in) / CHEN HUIQIN (Autor:in) / CHEN CHUQIAO (Autor:in) / YAN CHENGGANG (Autor:in)

    Erscheinungsdatum :

    2023-11-10


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    IPC:    B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL





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