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In order to improve smoothness and ride comfort of the vehicle, this paper proposes a Genetic Algorithm (GA) optimization method to address the subjectivity and limitations of performance optimization of Linear Quadratic Regulators (LQR) in the vertical dynamic system of vehicles. Firstly, a vertical dynamic model of the vehicle is established, an LQR controller is designed, and genetic algorithm is introduced for parameter optimization. The simulation results show that compared with passive suspension, the controller optimized by genetic algorithm demonstrates better control effect in performance index including body acceleration, suspension dynamic travel and tire dynamic displacement.

, authors=Ping Wang, Yiming Wang, authorsList=Ping Wang, Yiming Wang, authorCompany=null, correspAuthors=Ping Wang, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1308463001602908350, articleId=1308463001179283644, tenantId=1146029695717560320, journalId=1189918454225211397, language=CN, title=面向车辆垂向动力学LQR控制器的遗传算法优化, columnId=0, journalTitle=汽车工程师, columnName=, runingTitle=null, highlight=null, articleAbstract=

为改善整车平顺性和乘坐舒适性，针对车辆垂向动力学系统中线性二次型调节器（LQR）存在的性能优化主观性和局限性问题，提出了一种遗传算法（GA）优化方法。首先建立汽车垂向动力学模型，设计了LQR控制器，然后，引入遗传算法实现了参数优化。仿真结果显示，相较于被动悬架，经遗传算法优化的LQR控制器在车身加速度、悬架动行程以及轮胎动位移方面展现了更优的控制效果。

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