基于遗传算法优化的麦弗逊主动悬架模糊PID控制器设计  

Fuzzy-PID Control of Vehicle Active Macpherson Suspension Based on Genetic Algorithm Optimization

作　　者：刘月 刘功兴 何法 Liu Yue;Liu Gongxing;He Fa

机构地区：[1]辽宁省交通运输事业发展中心,辽宁沈阳110003 [2]东软睿驰汽车技术(沈阳)有限公司,辽宁沈阳110179

出　　处：《辽宁省交通高等专科学校学报》2022年第4期1-5,共5页Journal of Liaoning Provincial College of Communications

摘　　要：本文以麦弗逊主动悬架为研究对象,建立新型麦弗逊主动悬架模型,以汽车行驶平顺性和悬架稳定性作为评价指标,降低车身加速度幅值为控制目标,设计麦弗逊式悬架模型的模糊PID控制器,并利用遗传算法的全局收敛能力和并行寻优能力对模糊PID控制器的量化因子和控制器的修正系数进行多目标优化。对仿真结果进行分析能够得出,优化后的车身加速度和控制臂角位移的均方根值有所下降,间接地提高了车辆驾驶时的平顺性和悬架稳定性,验证了遗传算法对控制器的优化是有效的。It took active Macpherson suspension as the research object and established a new type of active Macpherson suspension model and took the vehicle ride comfort and suspension stability as the evalua-tion index.The fuzzy-PID controller of active Macpherson suspension model was designed to reduce the body acceleration amplitude.Then optimized the quantification factors and the correction coefficient of PID parameters by genetic algorithm with global convergence ability and parallel optimization ability.The simu-lation results show the RMS of body acceleration and control arm angular displacement value were de-creased,indirectly improved vehicle ride comfort and driving stability of suspension.The genetic algorithm is effective to optimization controller.

关 键 词：麦弗逊主动悬架模型 遗传算法 模糊PID 

分 类 号：U463.33[机械工程—车辆工程]