The invention provides a semi-active suspension LQR weight coefficient optimization method based on an improved grey wolf algorithm, and belongs to the field of automobile suspension systems. The optimization method comprises the following steps: carrying out an indicator diagram test on the magnetorheological damper, carrying out parameter identification, building a Dahl positive model, and building a magnetorheological damper inverse model by utilizing a fuzzy neural network; based on the magneto-rheological damper inverse model, an improved grey wolf algorithm is used for optimizing the weight coefficient of an LQR controller, and complete closed-loop feedback optimal control is formed; and operating the established 1/4 vehicle semi-active suspension model in MATLAB based on the optimized optimal control, carrying out time domain suspension performance evaluation analysis, and verifying that the controller effectively improves the smoothness and comfort of the vehicle. The improved grey wolf algorithm is used for optimizing the weight coefficient of the LQR controller, complete closed-loop feedback optimal control is formed, and the defect that in an LQR control strategy, the performance index weight coefficient needs to be selected manually is effectively overcome. And the established 1/4 vehicle semi-active suspension model is operated in MATLAB, time-domain suspension performance evaluation analysis is carried out, and it is verified that the controller can effectively improve the smoothness and comfort of the vehicle.

    本发明提供的一种基于改进灰狼算法的半主动悬架LQR权重系数优化方法,属于汽车悬挂系统领域。优化步为:对磁流变阻尼器进行示功图试验进行参数辨识搭建Dahl正模型,利用模糊神经网络搭建磁流变阻尼器逆模型;基于磁流变阻尼器逆模型,利用改进灰狼算法对LQR控制器权重系数进行优化并形成完整的闭环反馈最优控制;基于优化后的最优控制在MATLAB中运行已建立的1/4车辆半主动悬架模型,进行时域悬架性能评价分析,验证该控制器有效改善车辆的平顺性与舒适性。本发明利用改进灰狼算法对LQR控制器权重系数进行优化并形成完整的闭环反馈最优控制,有效解决LQR控制策略中性能指标权重系数需手动选取的不足。并在MATLAB中运行已建立的1/4车辆半主动悬架模型,进行时域悬架性能评价分析,验证该控制器可有效改善车辆的平顺性与舒适性。


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    Title :

    Semi-active suspension LQR weight coefficient optimization method based on improved grey wolf algorithm


    Additional title:

    一种基于改进灰狼算法的半主动悬架LQR权重系数优化方法


    Contributors:
    XIONG XIN (author) / CHEN CHANGZHUANG (author) / LIU YAMING (author) / YANG GANG (author)

    Publication date :

    2024-10-15


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G05B Steuer- oder Regelsysteme allgemein , CONTROL OR REGULATING SYSTEMS IN GENERAL / B60G VEHICLE SUSPENSION ARRANGEMENTS , Radaufhängungen und Federungen für Fahrzeuge / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen