游标类量具检定装置的驱动系统误差补偿

doi:10.3969/j.issn.1000-1158.2018.03.08

摘要
图/表
参考文献(18)
相关文章 (15)

全文: PDF (349 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要在游标类量具检定过程中,当检定装置的驱动系统的动态工作台处于低速运动状态时,由于与滚珠丝杠之间存在着摩擦和齿隙非线性的误差问题,导致无法将游标类量具精确地移动到检定规程所要求的检测点。为解决该误差问题,运用LuGre摩擦模型和自适应律周期性递归小波神经网络进行补偿,并根据李诺夫稳定性进行分析,保证了闭环系统的有界性和收敛性。仿真实验验证了位置跟踪性能的改善,将控制补偿方案在检定装置的驱动系统中进行了实验论证,结果检定装置正反行程的定位精度分别提高了47.6%和49.7%。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	陈旺达
	徐志玲
	厉志飞

关键词 ：计量学, 游标类量具, 驱动系统, 非线性补偿, 递归小波神经网络

Abstract：In the verification process of vernier measuring tools, when the dynamic table of the drive system in the verification device is at a low speed, the errors of the friction and backlash nonlinearity are exist between the dynamic work station and the ball screw, so the vernier measuring tools cannot be accurately moved to the test point required by the verification procedure. In order to solve the problem of the errors, the LuGre friction model and adaptive periodic recursive wavelet neural network are used to compensate the friction and backlash nonlinearity.Based on the Liroff stability analysis, the boundedness and convergence of the closed-loop system are guaranteed.The simulation results show that the performance of position tracking is improved, and the control compensation scheme is demonstrated in the driving system of the verification device, the accuracy of positive is improved by 47.6% in positive movement and 49.7% in negative movement.

Key words： metrology vernier gauge driving system nonlinear compensation recurrent wavelet neural networks

收稿日期: 2017-08-18 发布日期: 2018-04-12

PACS:

TB921

通讯作者: 陈旺达 E-mail: 1179745901@qq.com

作者简介: 陈旺达（1993-）,男,浙江宁波人,中国计量大学硕士研究生,研究方向为数字图像处理,自动化控制。cwangda@sina.com

引用本文:

陈旺达,徐志玲,厉志飞. 游标类量具检定装置的驱动系统误差补偿[J]. 计量学报, 2018, 39(3): 326-331.
CHEN Wang-da,XU Zhi-ling,LI Zhi-fei. Error Compensation of Drive System of Vernier Measuring Instrument. Acta Metrologica Sinica, 2018, 39(3): 326-331.

链接本文:

http://jlxb.china-csm.org:81/Jwk_jlxb/CN/10.3969/j.issn.1000-1158.2018.03.08 或 http://jlxb.china-csm.org:81/Jwk_jlxb/CN/Y2018/V39/I3/326

［1］刘丽兰,刘宏昭,吴子英.进给系统中速度爬行响应特征分析［J］.机械设计,2017,34(6):17-22.
Liu L L,Liu H Z,Wu Z Y.Response characteristic analysis of stick-slip velocity in feed system［J］.Journal of Machine Design,2017,34(6):17-22.
［2］赵国峰.一类齿隙非线性控制系统的研究［D］.南京:南京理工大学,2005.
［3］张鹏,李颖晖,肖蕾.基于递归神经网络的伺服系统自适应反步控制［J］.系统仿真学报,2008,20(6):1475-1478.
Zhang P, Li Y H, Xiao L.Adaptive-backstepping control for servo system based on recurrent-neural-network［J］.Journal of System Simulation,2008,20(6):1475-1478.
［4］许颖,于化东,于占江,等.微小摩擦测试系统设计［J］.计量学报,2013,34(5):452-456.
Xu Y, Yu H D, Yu Z J, et al.Design of the micro-friction testing system［J］.Acta Metrologica Sinica,2013,34(5):452-456.
［5］孙艳玲,常素萍.接触式表面轮廓测量的非线性误差分析与补偿［J］.计量学报,2016,37(6): 563-566.
Sun Y L, Chan S P.Analysis and compensation of the nonlinear error based on contact surface profil measurement ［J］.Acta Metrologica Sinica,2016,37(6): 563-566.
［6］向红标,谭文斌,李醒飞,等.基于LuGre模型的自适应摩擦补偿［J］.机械工程学报,2012,48(17):70-74.
Xiang H B, Tan W B, Li X F, et al.Adaptive friction compensation based on LuGre model［J］.Journal of Mechanical Engineering, 2012, 48(17): 70-74.
［7］周金柱,段宝岩,黄进.LuGre摩擦模型对伺服系统的影响与补偿［J］.控制理论与应用,2008,25(6):990-994.
Zhou J Z, Duan B Y, Huang J.Effect and compensation for servo systems using Lu Gre friction model［J］.Control Theory & Applications, 2008, 25(6):990-994.
［8］王洪斌,周振,王跃灵,等.非线性系统的有限时间扩张状态观测器的设计［J］.计量学报,2017,38(6): 725-729.
Wang H B, Zhou Z, Wang Y L, et al.Finite time extended state observer designed for nonlinear systems［J］.Acta Metrologica Sinica, 2017,38(6): 725-729.
［9］于占东,王庆超.一类不确定非线性系统反步自适应神经网络控制研究［J］.控制与决策,2004,19(5):561-564,569.
Yu Z D, Wang Q C.Adaptive backstepping neural control for a class of uncertain nonlinear systems［J］.Control and Decision,2004,19(5): 561-564, 569.
［10］黄俊朋.提高含齿隙伺服系统运动精度的控制研究［D］.哈尔滨:哈尔滨工业大学,2010.
［11］赵浩.一种自补偿差动式扭矩传感器的研究［J］.计量学报,2016,37(4): 394-397.
Zhao H.Study on self compensating differential torque sensor［J］.Acta Metrologica Sinica,2016,37(4): 394-397.
［12］杨帆.基于LuGre摩擦模型的伺服系统自适应鲁棒控制研究［D］.南京:南京理工大学,2012.
［13］Fang Y, Chow T W S, Li X D.Use of a recurrent neural network in discrete sliding-mode control［J］.IEE Proceedings-Control Theory and Applications,1999,146（1）:84-99.
［14］Lin F J, Wai R J, Hong C M.Recurrent neural network control for LCC-resonant ultrasonic motor drive［J］.IEEE Trans Ultrason Ferroelectr Freq Control, 2000, 47（3）: 737-49.
［15］包达飞,汤文成,董亮.带摩擦补偿的滚珠丝杠副进给系统自适应滑模控制［J］.东南大学学报(自然科学版),2015,45(3):455-460.
Bao D F, Tang W C, Dong L.Adaptive sliding mode control of ball screw drives with friction compensation［J］.Journal of Southeast University (Natural Science Edition),2015,45(3):455-460.
［16］马艳玲,黄进,张丹.伺服系统中齿隙非线性的自适应补偿［J］.系统仿真学报,2009,21(5):1498-1504.
Ma Y L, Huang J, Zhang D.Adaptive Compensation of Backlash Nonlinearity for Servo Systems［J］.Journal of System Simulation,2009,21(5):1498-1504.
［17］周艳秋.步进电机定位控制技术的研究［D］.大连:大连交通大学,2009.
［18］Yough K D.A variable structure control approach to friction force compensation［C］//American Control Conferenee, USA,Philadelphia ,1998:3138-3142.