第40卷第3期计算机应用与软件Vol.40No.32023年3月ComputerApplicationsandSoftwareMar.2023融合社会学习和莱维飞行的QPSO自平衡控制参数优化董慧芬沈鹏飞(中国民航大学机器人研究所控制科学与工程天津300300)收稿日期:2020-06-18。天津市自然科学基金项目(17JCYBJC18200)。董慧芬,副教授,主研领域:电力电子及电机控制,飞机供电系统及机器人控制。沈鹏飞,硕士生。摘要非同轴两轮自平衡车LQR控制器Q、R矩阵整定过程,QPSO存在信息共享机制单一等问题,提出融合社会学习、莱维飞行的改进QPSO。建立平衡车动力学模型,根据适应度函数采用动态线性递减LSL-QPSO进行Q、R优化,对LSL-QPSO控制进行仿真。结果表明:改进LSL-QPSO控制更加有效,相对于QPSO,起摆倾角和进动角峰值分别降低18.2%和21%,调节时间分别缩短16.6%和14.3%;抗干扰倾角和进动角的调节时间分别缩短20%和12.5%,进动角峰值降低15.2%,有效提升系统动态性能。关键词陀螺平衡车量子粒子群线性二次型调节器社会学习莱维飞行中图分类号TP18文献标志码ADOI:10.3969/j.issn.1000-386x.2023.03.015PARAMETEROPTIMIZATIONOFSELF-BALANCINGCONTROLLERBASEDONQPSOINTEGRATINGSOCIALLEARNINGANDLEVYFLIGHTDongHuifenShenPengfei(ControlScienceandEngineering,InstituteofRobotics,CivilAviationUniversityofChina,Tianjin300300,China)AbstractIntheprocessoftuningQandRmatrixoftheLQRcontrollerofaself-balancingcar,theQPSOhasaproblemofsimpleinformationsharingmechanism.Tosolvethisproblem,animprovedQPSOintegratingsociallearningandLevyflightisproposed.Thedynamicmodelofthebalancecarwasestablished.AlineardecreasingLSL-QPSOwasusedtodesignQandRoptimizationbasedonthefitnessfunction.TheLSL-QPSOwassimulated.TheresultsshowthattheimprovedLSL-QPSOismoreeffective.ComparedwithQPSO,thepeaktiltangleisreducedby18.2%andtheadjustmenttimeisshortenedby16.6%.Theprecessionanglepeakisreducedby21%,andtheadjustmenttimeisshortenedby14.3%.Theadjustmenttimeofanti-interferencetiltangleisshortenedby20%.Andthepeakofprecessionangleisreducedby15.2%,andtheadjustmenttimeisshortenedby12.5%.KeywordsGyrobalancecarQuantumparticleswarmLinearquadraticregulatorSociallearningLevyflight0引言非同轴两轮力矩陀...