基于遗传算法的主动悬架最优控制研究  被引量:4

Research on Optimal Control of Active Suspension Based on Genetic Algorithm

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作  者:谢伟 赵波[1] 蒋培露 Xie Wei;Zhao Bo;Jang Peilu(College of Vehicle Engineering,Shanghai University of Engineering Science,Shanghai 201620,China;IAT automobile Co.,Ltd.,Shanghai 201821,China)

机构地区:[1]上海工程技术大学汽车工程学院,上海市201620 [2]阿特尔汽车有限公司,上海市201821

出  处:《农业装备与车辆工程》2019年第8期78-81,共4页Agricultural Equipment & Vehicle Engineering

摘  要:为了提高主动悬架LQG 控制策略的设计效率和准确性,以及验证主动悬架的优越性,建立了1/4主动悬架动力学模型。控制策略选取了线性二次型最优控制(LQG),通过遗传算法(GA)确定了LQG控制器的加权系数,最后采用MATLAB/Simulink 软件进行了仿真验证。结果显示:采用GA 确定LQG 控制器的加权系数的方法是合理的;与被动悬架相比,主动悬架的车身垂直加速度显著降低了,改善了汽车行驶平顺性。此方法为悬架的LQG 控制策略的实际应用提供了参考。In order to improve the design efficiency and accuracy of active suspension LQG control strategy and verify the advantages of active suspension, a dynamics model of one-fourth active suspension model was established. The control strategy elects the linear quadratic optimal control (LQG) and determines the linear quadratic optimal controller (LQG) scheme of the weighted coefficient through the genetic algorithm (GA). Finally, the MATLAB/Simulink software is used for simulation, and the results show: using the method of GA to determine the weighting coefficient of LQG controller scheme is reasonable. Compared with the passive suspension, the vertical acceleration of the vehicle body of the active suspension is significantly decreased, which improves the smoothness of the vehicle. It provides a reference for the practical application of LQG control strategy of suspension.

关 键 词:主动悬架 LQG 控制 遗传算法 仿真 

分 类 号:U463.33[机械工程—车辆工程]

 

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