Article(id=1228011510107140543, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228011505698931621, articleNumber=null, orderNo=null, doi=10.16385/j.cnki.issn.1004-4523.2024.01.001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1647187200000, receivedDateStr=2022-03-14, revisedDate=1656345600000, revisedDateStr=2022-06-28, acceptedDate=null, acceptedDateStr=null, onlineDate=1770710359360, onlineDateStr=2026-02-10, pubDate=1706371200000, pubDateStr=2024-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770710359360, onlineIssueDateStr=2026-02-10, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770710359360, creator=13701087609, updateTime=1770710359360, updator=13701087609, issue=Issue{id=1228011505698931621, tenantId=1146029695717560320, journalId=1225147924628267009, year='2024', volume='37', issue='1', pageStart='1', pageEnd='190', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1770710358308, creator=13701087609, updateTime=1770795378159, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1228368104862974870, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228011505698931621, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1228368104862974871, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228011505698931621, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=10, ext={EN=ArticleExt(id=1228011510434296266, articleId=1228011510107140543, tenantId=1146029695717560320, journalId=1225147924628267009, language=EN, title=Vibration suppression strategy for dual-flexible manipulator using disturbance compensation fuzzy setting control method, columnId=null, journalTitle=Journal of Vibration Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

The variable-length dual-flexible manipulator is composed of a flexible joint and a flexible load,which is affected by flexibility,friction,and time variation of parameters. It will vibrate in the process of moving,which will reduce the tracking accuracy of the end-effector. In this paper,the fuzzy tuning PI control strategy based on disturbance observer is used to control the output speed of the dual-flexible manipulator servo system. The vibration of the manipulator can be suppressed indirectly by controlling the speed fluctuation of the flexible load. Based on the assumed modal method and the Lagrange principle,the dynamic equations of the dual-flexible manipulator are established. A low pass filter in the disturbance observer is designed according to the robust stability theorem,so that the disturbance observer can satisfy the stability of the controller parameter time-varying and the controlled object parameter perturbation jointly. The effectiveness of the proposed method is verified by numerical simulation and control experiments of the dual-flexible manipulator servo system. The experimental results show that the proposed control strategy can better eliminate the influence of parameter time-varying and flexibility on the output speed,and improve the control precision of the end-effector.

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双柔性机械臂由柔性关节和变长度的柔性负载组成,会同时受到柔性、摩擦和参数时变的影响,在运动过程中,它会出现振动的现象,导致末端执行器的跟踪精度降低。本文采用基于干扰观测器的模糊整定PI策略控制双柔性机械臂伺服系统的输出转速,通过控制柔性负载的转速波动间接抑制机械臂的振动。根据假设模态法和拉格朗日原理建立了考虑变形的双柔性机械臂伺服系统的动力学方程。根据鲁棒稳定性理论设计干扰观测器中的低通滤波器,使干扰观测器同时满足控制器参数时变和受控对象参数摄动的稳定性。通过数值仿真分析和双柔性机械臂伺服系统控制实验,验证了所提方法的有效性。实验结果表明,本文提出的控制策略可以更好地消除参数时变和柔性对于输出转速的影响,提高末端执行器的控制精度。

, correspAuthors=null, authorNote=null, correspAuthorsNote=
李小彭(1976―),男,博士,教授。E-mail:
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尚东阳(1995—),男,博士研究生。E-mail:

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尚东阳(1995—),男,博士研究生。E-mail:

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ArticleFig(id=1228042474963272634, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=CN, label=图9, caption=双柔性机械臂伺服系统控制实验结果, figureFileSmall=mE9vLDTkKUc/uLPcJmCZZA==, figureFileBig=KyjulH2gSgio2isupIXnmA==, tableContent=null), ArticleFig(id=1228042475072324542, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=EN, label=Tab. 1, caption=

Parameters of the low-pass filter

, figureFileSmall=null, figureFileBig=null, tableContent=
参数低通滤波器系数是否满足公式(16)
abc
Q1(s)111
Q2(s)110.1
Q3(s)10.10.1
), ArticleFig(id=1228042475164599234, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=CN, label=表1, caption=

低通滤波器参数

, figureFileSmall=null, figureFileBig=null, tableContent=
参数低通滤波器系数是否满足公式(16)
abc
Q1(s)111
Q2(s)110.1
Q3(s)10.10.1
), ArticleFig(id=1228042475265262534, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=EN, label=Tab. 2, caption=

Fuzzy rules for controller parameters kp

, figureFileSmall=null, figureFileBig=null, tableContent=
kpec
NBNMNSZEPSPMPB
eNBPBPBPMPMPSZEZE
NMPBPBPMPSPSZENS
NSPMPMPMPSZENSNS
ZEPMPMPSZENSNMNM
PSPSPSZENSNSNMNM
PMPSZENSNSNMNMNB
PBZEZENMNMNMNBNB
), ArticleFig(id=1228042475403674572, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=CN, label=表2, caption=

控制器参数kp的模糊规则

, figureFileSmall=null, figureFileBig=null, tableContent=
kpec
NBNMNSZEPSPMPB
eNBPBPBPMPMPSZEZE
NMPBPBPMPSPSZENS
NSPMPMPMPSZENSNS
ZEPMPMPSZENSNMNM
PSPSPSZENSNSNMNM
PMPSZENSNSNMNMNB
PBZEZENMNMNMNBNB
), ArticleFig(id=1228042475563058130, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=EN, label=Tab. 3, caption=

Fuzzy rules for controller parameter ki

, figureFileSmall=null, figureFileBig=null, tableContent=
kiec
NBNMNSZEPSPMPB
eNBNBNBNMNMNSZEZE
NMNBNBNMNSNSZEZE
NSNBNMNSNSZEPSPS
ZENMNMNSZEPSPMPM
PSNMNSZEPSPSPMPB
PMZEZEPSPSPMPBPB
PBZEZEPSPMPMPBPB
), ArticleFig(id=1228042475672110037, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=CN, label=表3, caption=

控制器参数ki的模糊规则

, figureFileSmall=null, figureFileBig=null, tableContent=
kiec
NBNMNSZEPSPMPB
eNBNBNBNMNMNSZEZE
NMNBNBNMNSNSZEZE
NSNBNMNSNSZEPSPS
ZENMNMNSZEPSPMPM
PSNMNSZEPSPSPMPB
PMZEZEPSPSPMPBPB
PBZEZEPSPMPMPBPB
), ArticleFig(id=1228042475768579034, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=EN, label=Tab. 4, caption=

Parameters of the dual-flexible manipulator servo system

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参数长度1长度2
柔性连杆长度l/m1.52
柔性连杆质量m/kg11
柔性连杆抗弯刚度EI/(N∙m28080
柔性连杆线密度ρA/(kg∙m-10.6670.5
柔性连杆转动惯量Jl/(kg∙m20.751.333
柔性连杆模态频率ω1/(rad∙s-117.11611.117
模态函数特征根值β11.250.9375
电机端转动惯量Jm/(kg∙m22
扭转刚度Ks/(N∙rm∙rad-1500
初始控制器参数KP=15;KI=20
终止控制器参数KP=20;KI=30
低通滤波器参数a=1;b=0.1;c=0.1
), ArticleFig(id=1228042475911185374, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228011510107140543, language=CN, label=表4, caption=

双柔性机械臂伺服系统参数

, figureFileSmall=null, figureFileBig=null, tableContent=
参数长度1长度2
柔性连杆长度l/m1.52
柔性连杆质量m/kg11
柔性连杆抗弯刚度EI/(N∙m28080
柔性连杆线密度ρA/(kg∙m-10.6670.5
柔性连杆转动惯量Jl/(kg∙m20.751.333
柔性连杆模态频率ω1/(rad∙s-117.11611.117
模态函数特征根值β11.250.9375
电机端转动惯量Jm/(kg∙m22
扭转刚度Ks/(N∙rm∙rad-1500
初始控制器参数KP=15;KI=20
终止控制器参数KP=20;KI=30
低通滤波器参数a=1;b=0.1;c=0.1
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采用干扰补偿模糊整定的双柔性机械臂抑振策略
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尚东阳 1 , 李小彭 1 , 尹猛 2 , 李凡杰 1
振动工程学报 | 2024,37(1): 1-10
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振动工程学报 | 2024, 37(1): 1-10
采用干扰补偿模糊整定的双柔性机械臂抑振策略
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尚东阳1 , 李小彭1 , 尹猛2, 李凡杰1
作者信息
  • 1东北大学机械工程与自动化学院,辽宁 沈阳 110819
  • 2中国科学院深圳先进技术研究院,广东 深圳 518055
  • 尚东阳(1995—),男,博士研究生。E-mail:

通讯作者:

李小彭(1976―),男,博士,教授。E-mail:
Vibration suppression strategy for dual-flexible manipulator using disturbance compensation fuzzy setting control method
Dong-yang SHANG1 , Xiao-peng LI1 , Meng YIN2, Fan-jie LI1
Affiliations
  • 1School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China
  • 2Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
出版时间: 2024-01-28 doi: 10.16385/j.cnki.issn.1004-4523.2024.01.001
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双柔性机械臂由柔性关节和变长度的柔性负载组成,会同时受到柔性、摩擦和参数时变的影响,在运动过程中,它会出现振动的现象,导致末端执行器的跟踪精度降低。本文采用基于干扰观测器的模糊整定PI策略控制双柔性机械臂伺服系统的输出转速,通过控制柔性负载的转速波动间接抑制机械臂的振动。根据假设模态法和拉格朗日原理建立了考虑变形的双柔性机械臂伺服系统的动力学方程。根据鲁棒稳定性理论设计干扰观测器中的低通滤波器,使干扰观测器同时满足控制器参数时变和受控对象参数摄动的稳定性。通过数值仿真分析和双柔性机械臂伺服系统控制实验,验证了所提方法的有效性。实验结果表明,本文提出的控制策略可以更好地消除参数时变和柔性对于输出转速的影响,提高末端执行器的控制精度。

振动控制  /  柔性机械臂  /  干扰观测器  /  模糊整定  /  PI控制

The variable-length dual-flexible manipulator is composed of a flexible joint and a flexible load,which is affected by flexibility,friction,and time variation of parameters. It will vibrate in the process of moving,which will reduce the tracking accuracy of the end-effector. In this paper,the fuzzy tuning PI control strategy based on disturbance observer is used to control the output speed of the dual-flexible manipulator servo system. The vibration of the manipulator can be suppressed indirectly by controlling the speed fluctuation of the flexible load. Based on the assumed modal method and the Lagrange principle,the dynamic equations of the dual-flexible manipulator are established. A low pass filter in the disturbance observer is designed according to the robust stability theorem,so that the disturbance observer can satisfy the stability of the controller parameter time-varying and the controlled object parameter perturbation jointly. The effectiveness of the proposed method is verified by numerical simulation and control experiments of the dual-flexible manipulator servo system. The experimental results show that the proposed control strategy can better eliminate the influence of parameter time-varying and flexibility on the output speed,and improve the control precision of the end-effector.

vibration control  /  flexible manipulator  /  disturbance observer  /  fuzzy setting  /  PI control
尚东阳, 李小彭, 尹猛, 李凡杰. 采用干扰补偿模糊整定的双柔性机械臂抑振策略. 振动工程学报, 2024 , 37 (1) : 1 -10 . DOI: 10.16385/j.cnki.issn.1004-4523.2024.01.001
Dong-yang SHANG, Xiao-peng LI, Meng YIN, Fan-jie LI. Vibration suppression strategy for dual-flexible manipulator using disturbance compensation fuzzy setting control method[J]. Journal of Vibration Engineering, 2024 , 37 (1) : 1 -10 . DOI: 10.16385/j.cnki.issn.1004-4523.2024.01.001
同时考虑关节柔性和负载柔性的机械臂称为双柔性机械臂,它由柔性关节和柔性负载组成1。变长度的双柔性机械臂同时具有移动关节和转动关节,依靠转动关节实现大范围的运动,依靠移动关节改变机械臂长度实现精确抓取物体。随着机械臂的伸长,其线密度逐渐减小,变长度的双柔性机械臂在转动过程中更容易产生变形。随着机械臂的不断发展,具有轻质、大回转半径的双柔性机械臂应用于航空航天、工业装配、核电设备检修等诸多领域2-3。文献[4]将变长度的柔性机械臂应用于协作机器人,设计开发了柔性协作机械臂。
变长度的双柔性机械臂是多输入、多输出的复杂非线性时变系统,其建模方法可以借鉴柔性机械臂和柔性关节的动力学模型。柔性机械臂的动力学建模方法有:有限元法、哈密顿原理和假设模态法等。文献[5-6]使用有限元法将柔性机械臂等效为欧拉-伯努利梁模型建立柔性机械臂的动力学方程。文献[7]使用哈密顿原理建立具有轴向伸缩运动的柔性机械臂的动力学模型。文献[8-9]使用假设模态建立了柔性机械臂的动力学方程。但上述文献中尚未考虑柔性关节的影响。文献[10]使用有限元法建立了同时包含柔性负载和柔性关节的机械臂的动力学方程。在描述柔性机械臂的变形问题时,通常忽略纵向变形,主要考虑横向变形。随着柔性机械臂动力学研究的逐渐深入,其纵向变形问题逐渐得到关注。文献[11]在建立刚柔耦合双连杆机械臂动力学模型的过程中考虑了二维变形的影响。文献[12-13]将柔性关节等效为双惯量模型,并且考虑了摩擦力矩对传动的影响。由此可知,双柔性机械臂可以等效为含有柔性负载的双惯量系统。
变长度的双柔性机械臂在运动过程中会出现横向振动,进而影响机械臂的运动精度,可以采用主动控制策略来抑制双柔性机械臂的振动。所谓的主动控制方法,是通过改变控制器参数或控制器结构使双柔性机械臂获得稳定的输出,进而减弱振动。根据文献[14-15]可知,在不考虑外界载荷的情况下,柔性机械臂的振动程度与转角的加速度密切相关。因此,可以通过减小转角的速度波动,进而减弱振动。为了消除伺服系统中摩擦力矩的影响,干扰观测器被广泛地应用于柔性机械臂的伺服控制中。文献[16-17]使用干扰观测器辨识并补偿摩擦力矩,进而提高柔性机械臂的控制精度。相较于固定长度的机械臂,变长度的机械臂具有明显的参数时变特性。动力学参数的时变会造成伺服系统输出转速的波动。随着智能控制理论的发展,模糊控制和神经网络控制被应用于时变系统中。文献[14]使用RBF神经网络补偿柔性机械臂动力学方程中的不确定部分,以此提高控制精度。基于模糊规则整定的控制策略可以实时改变控制器参数,进而提高受控对象的运动精度。
本文使用假设模态法建立了考虑LuGre摩擦模型和横向变形的双柔性机械臂伺服系统的动力学方程;采用基于干扰观测器的模糊控制策略减小伺服系统输出速度的波动,进而抑制振动。其中控制器的参数根据模糊规则进行实时调整。控制器和受控对象参数的时变特性会对干扰观测器的稳定性造成影响,故根据鲁棒稳定性理论设计干扰观测器的低通滤波器。通过干扰观测器对外界干扰进行补偿,减弱伺服系统输出速度的波动。本文的主要贡献是:与文献[15]相比,本文建立了考虑摩擦和纵向变形的双柔性机械臂伺服系统动力学模型,且将机械臂的伸缩运动考虑在内;使用基于干扰观测器的模糊控制策略抑制双柔性机械臂的振动,相较于文献[113],本文提出的控制策略是在以上文献研究方法的基础上,综合考虑控制器参数和受控对象的时变特性,加入模糊控制以保持系统的时变特性。
本文所建立的双柔性机械臂伺服系统由伺服电机、柔性关节和柔性负载组成。其中,柔性关节一端连接伺服电机,另一端连接柔性负载。柔性负载在柔性关节的驱动下,在水平面内做旋转运动。柔性负载可以等效为欧拉-伯努利梁模型。双柔性机械臂伺服系统的示意图如图1所示。图1中,Tm表示驱动力矩;Ts表示轴矩;Mf表示电机端的摩擦力矩;θm为电机转角;θl为柔性负载转角;Ks为柔性关节扭转刚度;XOY表示静态坐标系;x0Oy0表示随动坐标系;wxt)表示横向变形,其中x表示随动坐标系的横坐标;Jm表示电机端的转动惯量。
根据文献[15],柔性负载的变形可以认为是模态函数和模态坐标的二维函数,其表达式如下式所示:
式中  表示第i阶模态函数;ηit)表示第i阶模态坐标;βi表示第i阶模态函数特征根值;l表示柔性负载长度;EI表示抗弯刚度;ρ表示体密度;A表示横截面积;ωi表示柔性负载的第i阶固有频率。
柔性负载上任意一点的向量,如下式所示:
根据式(2),可得到双柔性机械臂伺服系统的动能表达式如下式所示:
式中  。为了方便书写,用“”表示对时间的偏导数,用“'”表示对横坐标x的偏导数。
同理,可得到双柔性机械臂伺服系统的势能表达式如下式所示:
根据文献[14-15],忽略高阶模态的影响,应用拉格朗日方程可得到双柔性机械臂伺服系统的动力学方程,如下式所示:
其中:
双柔性机械臂伺服系统动力学方程中的摩擦力矩可以用LuGre模型描述,其表达式如下式所示:
式中  z表示接触面鬃毛的平均变形;σ0表示摩擦刚性系数;σ1表示摩擦阻尼系数;σ2表示黏性摩擦系数;Mc表示库伦摩擦力矩;Ms表示静摩擦力矩;θs表示Stribeck速度。
机械臂的伺服系统多采用三环控制策略,其中速度外环和电流内环的带宽差别较大。因此假设速度外环调节时电流内环已经完成调节,根据文献[13]可以忽略电流内环的影响。若使用固定参数的控制器无法使不同长度的柔性机械臂伺服系统获得稳定的转角输出,随着模糊控制的不断发展,可以使用模糊规则整定PI控制器参数对时变系统进行实时控制,使伺服系统获得平稳的转角输出。
伺服系统中摩擦力矩模型的参数难以确定,因此摩擦力矩无法准确地获得。摩擦力矩和其他未知的干扰统称为受控系统的外界干扰。在机械臂的伺服系统中可以增加干扰观测器对外界干扰进行辨识和补偿,由此消除外界干扰的影响。设计干扰观测器的核心环节是低通滤波器的设计,控制器参数的变化和受控对象动力学参数的时变为低通滤波器的设计带来困难。本文通过鲁棒稳定性理论设计低通滤波器的参数。
为了使用基于干扰观测器的模糊自适应PI控制策略对双柔性机械臂伺服系统进行控制,首先应该了解双柔性机械臂伺服系统的传动特性。
在忽略摩擦力矩和非线性项的情况下,对式(5)进行拉普拉斯变换,如下式所示:
式中  s表示拉普拉斯算子。
柔性负载的长度在变化,因此实际的传递函数和名义的传递函数存在差异,实际模型传递函数如下式所示:
式中 用“ˆ”表示实际参数的估计值;ωm表示伺服电机转速。其中,传递函数中的系数为:
式(8)在实际模型和名义模型之间存在着一定的误差。根据文献[16],假设名义模型和实际模型之间的关系可以用乘积摄动描述,如下式所示:
式中  表示名义模型传递函数;s)表示实际模型对名义模型的摄动。
为解决外界干扰对于双柔性机械臂伺服系统的影响,本文使用干扰观测器观测并补偿摩擦力矩。基于干扰观测器的双柔性机械臂伺服系统的转速控制框图如图2所示。图2中,表示电机理想转速;Cs)表示控制器;Qs)表示低通滤波器;ξ表示测量噪声;upi表示控制器输出;表示干扰观测器的输出;ψ表示未知干扰
根据文献[16]可以得到整个闭环系统关于参数摄动的补灵敏度函数,如下式所示:
若保证整个系统在参数摄动情况下稳定,应满足下式:
式中  WUs)表示上极限函数。
根据文献[16],上极限函数的选择应满足下式:
式(11)可以写成下式的形式:
如果低通滤波器需满足式(13),则下式必然成立:
选择等效权重函数WQs)使之满足下式:
其中,等效权重函数根据名义模型和控制器适当选取。根据式(15),低通滤波器的设计条件转变为下式:
根据文献[116],低通滤波器采用下式所示的形式:
式中  abc表示低通滤波器系数。
因为本文采用的是模糊规则整定控制器参数,所以控制器Cs)是变化的。假设初始时刻受控对象的实际传递函数可以用Gp1s)表示;控制器可以用C1s)表示。同理假设终止时刻受控对象的实际传递函数可以用Gp2s)表示;控制器可以用C2s)表示。由此可以确定Δ1s),Δ2s);E1s),E2s);WUs),WQs);其中,WUs)和WQs)应满足下式:
根据图3可知,Q1s)和Q2s)的曲线与Ws)的曲线相交,这表明,Q1s)和Q2s)的取值不满足式(16),低通滤波器此时的参数不满足鲁棒稳定性。当低通滤波器参数为Q3s)时,Q3s)曲线与Ws)的曲线相离,这可以保证系统的鲁棒稳定性。由此,可通过调整低通滤波器的参数保证式(18)成立。图3中低通滤波器参数的取值如表1所示。
本文所研究的受控对象是时变的,可根据Gn1s)确定初始状态下最优的PI控制器参数。此时的最优PI控制参数定义为KP1KI1。同理,根据Gn2s)可以获得终止状态下的最优PI控制器参数KP2KI2。根据KP1KI1KP2KI2可以获得控制器参数的变化范围,为使用模糊控制策略做好准备。
基于模糊规则整定的PI控制器以误差和误差变化率作为输入。控制器的输入变量和输出变量的模糊论域为[-6,6];实际输入误差的论域设定为[-0.1,0.1];实际输入误差变化率的论域为[-0.2,0.2];实际输出控制器的论域为[KP1 KP2]和[KI1 KI2]。由此可以求出误差、误差变化率和控制器参数的量化因子。模糊控制器输入和输出的模糊集设定为6个,如下式所示:
式中  e表示误差;ec表示误差变化率;N表示正;P表示负;B表示大;M表示适中;S表示小;ZE表示0。
本文选择高斯函数作为模糊控制器输入变量和输出变量的隶属度函数,如图4所示。控制器参数的模糊规则如表23所示。
根据模糊推理关系可以确定PI控制的参数,如下式所示:
式中  表示控制器参数的量化因子;kpki表示模糊规则的输出。
根据图2和PI控制器的控制律可得到下式:
根据式(21)和图2,在考虑外界未知干扰的情况下,双柔性机械臂伺服系统电机端的传递关系如下式所示:
根据式(22)可得到下式:
定义下式成立:
式中  K为常数向量;E为误差向量;Y为输入向量;表示电机期望转速;表示电机期望转角;k0k1表示正数。
根据式(23)和(24)可得到下式:
式中  表示最优的驱动力矩。
为了获得较好的控制效果,电机驱动力矩应该接近最优的驱动力矩。根据式(23)和(24)可得到下式:
根据式(26)可得到下式:
将式(27)写成下式的形式:
定义李雅普诺夫函数,如下式所示:
式中  P表示正定矩阵,满足下式:
式中  Q是一个正定矩阵,它的最小特征值满足
根据式(29)可得到下式:
根据式(31)可知,可通过调整PI控制器参数,进而改变upi,以保证系统的闭环稳定性。变长度的双柔性机械臂伺服系统的控制框图如图5所示。图中Δke和Δkec分别表示误差和误差变化律的量化因子。
本文对双柔性机械臂在两种不同长度情况下开展数值仿真实验。双柔性机械臂伺服系统的参数如表4所示。
在长度1的工况下,分别使用基于干扰观测器的模糊规则整定的PI控制策略(FCPI+DOB)、模糊整定的PI控制策略(FCPI)和PI控制策略(PI)对双柔性机械臂进行控制。以单位正弦函数作为额定转速输入伺服系统,可得到不同控制策略的仿真结果,如图6所示。
图6可知,在长度1的工况情况下,使用本文提出的控制策略能够获得稳定的转速输出,并且拥有最小的误差。根据图6(b)可知,使用干扰观测器的控制策略能够减少摩擦力矩所引起的误差突变;对比PI和FCPI对电机转速误差、负载转速和转角的影响,可以明显看出:时变的模糊规则整定控制器参数能大幅减小上述三种输出结果的波动,证明了模糊整定控制器参数对抑制系统振动的有效性。
因此,根据图6可知,本文使用的控制策略可以明显地改善双柔性机械臂输出转速和转角的波动。为研究不同控制策略在不同负载长度下对于双柔性机械臂的振动抑制效果,分别使用长度1和长度2的参数得到柔性负载末端变形随时间的变化规律,如图7所示。
根据图7可知,随着柔性负载长度的增加,负载柔性对于伺服系统的影响逐渐加强。单独使用模糊控制策略,在长度2的工况下末端变形量出现明显的波动。但是将干扰观测器和模糊控制联合使用的控制策略有效地减少了末端变形量的波动。通过图67可知,双柔性机械臂负载转角的波动程度与末端变形量的波动呈现正相关,因此可以通过间接控制负载转角的波动抑制机械臂的振动。
为验证本文所提出的基于干扰观测器的模糊控制策略的有效性,搭建了双柔性机械臂伺服系统的实验平台,如图8所示。在柔性机械臂控制实验平台中,多使用柔性梁模型代替柔性机械臂18
实验平台由电机、套索传动关节和可变长度的柔性梁组成。通过套索将伺服电机产生的驱动力矩传递到柔性梁(即柔性机械臂),驱动柔性梁转动。套索传动具有柔性,因此可以等效为柔性关节1。柔性机械臂由固定臂和伸缩臂组成,通过伸缩臂与固定臂不同位置的螺栓连接实现变长度。实验平台选用LabVIEW软件编写控制程序,并通过NI-Crio-9053作为下位机将控制信号输入NI-9264模块产生对应的脉冲信号,控制电机输出力矩。实验平台通过磁编码器采集电机和负载的转角信号,并通过NI-9401数据采集模块将信号传入控制系统,由此实现反馈控制。
为了研究不同长度的双柔性伺服系统的控制效果,本文选择不同的位置连接固定柔性臂和伸缩臂,以此模拟相同质量、不同长度的柔性负载。设置两种不同长度的柔性负载开展控制实验。其中,双柔性机械臂伺服系统的参数和控制器的参数如表4所示。分别使用上述三种不同的控制策略对双柔性伺服系统进行控制。在控制实验中,选择单位正弦函数作为电机期望转速。由于柔性负载的变形难以直接测量,本文通过柔性负载末端的加速度表征振动。由此,可以得到不同控制策略下,双柔性机械臂伺服系统的实验结果,如图9所示。
根据图9可知,当双柔性机械臂处于两种不同长度时,三种控制策略结果接近,都能获得稳定的跟踪效果。但是没有使用干扰观测器的控制策略受到外界干扰的影响会引起误差波动,而使用干扰观测器可以有效地消除外界干扰的影响。通过对比图9(c)和(f)可知,随着柔性负载长度的增加,使用固定参数的控制器加速度波动明显。但是使用基于干扰观测器的模糊自适应控制策略能有效地减小加速度的波动,具有更好的抑振效果。
通过控制实验可知,使用基于干扰观测器的模糊控制策略能够有效地减小转角的波动,进而减弱双柔性机械臂的振动。相比于PI控制策略,本文所提出的控制策略能够使误差绝对值的平均值降低13.415%。在长度2情况下,本文所提出的控制策略能够使误差绝对值的平均值降低9.264%;使误差标准差降低15.298%;使柔性机械臂末端横向加速度降低16.28%。根据上述统计数据可以证明本文所提出的控制策略能有效地提高双柔性机械臂的控制精度。
本文建立了考虑横向变形的双柔性机械臂伺服系统的动力学模型,并应用基于干扰观测器的模糊整定的PI控制策略来减小伺服系统输出速度的波动,进而抑制双柔性机械臂的振动。所设计的控制器参数根据模糊规则随着柔性负载的长度变化而变化。并使用干扰观测器对外界干扰进行观测和补偿,以减少摩擦力矩对双柔性机械臂的影响。通过仿真分析和实验表明:本文所提出的控制策略能够有效地抑制双柔性机械臂的振动,提高末端执行器的运动精度。具体结论如下:
(1)长度可变的柔性机械臂会导致伺服系统参数具有显著的时变特性,增强了系统的鲁棒性。在设计干扰观测器的过程中需要考虑动力学参数的时变特性。通过本文提出的低通滤波器设计方法可以保证变参数系统的鲁棒稳定性。
(2)本文所提出的控制策略可以有效地提高柔性机械臂转角的控制精度。相比于传统的PI控制策略,本文所提出的控制策略能够使转角误差降低13.415%;使柔性机械臂末端横向加速度降低16.28%。
  • 国家自然科学基金资助项目(51875092)
  • 国家重点研发计划项目(2020YFB2007802)
  • 中央高校基本科研业务费专项资金资助项目(N2103025)
  • 宁夏回族自治区自然科学基金资助项目(2020AAC03279)
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2024年第37卷第1期
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doi: 10.16385/j.cnki.issn.1004-4523.2024.01.001
  • 接收时间:2022-03-14
  • 首发时间:2026-02-10
  • 出版时间:2024-01-28
补充材料
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出版历史
  • 收稿日期:2022-03-14
  • 修回日期:2022-06-28
基金
国家自然科学基金资助项目(51875092)
国家重点研发计划项目(2020YFB2007802)
中央高校基本科研业务费专项资金资助项目(N2103025)
宁夏回族自治区自然科学基金资助项目(2020AAC03279)
作者信息
    1东北大学机械工程与自动化学院,辽宁 沈阳 110819
    2中国科学院深圳先进技术研究院,广东 深圳 518055

通讯作者:

李小彭(1976―),男,博士,教授。E-mail:
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https://castjournals.cast.org.cn/joweb/zdgcxb/CN/10.16385/j.cnki.issn.1004-4523.2024.01.001
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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