Please wait a minute...
投稿  |   English  | 
   首页  |  最新收录  |  当期目录  |  过刊浏览  |  作者中心  |  关于期刊   开放获取  
投稿  |   English  | 
Engineering    2017, Vol. 3 Issue (5) : 641-647
Research |
1. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an 710054, China
2. Collaborative Innovation Center of High-End Manufacturing Equipment, Xi’an Jiaotong University, Xi’an 710054, China
全文: PDF(1626 KB)   HTML
导出: BibTeX | EndNote | Reference Manager | ProCite | RefWorks     支持信息
制策略。MCM 由峰值滤波器和陷波滤波器组成,从而将设备动态变为虚拟同位系统,且可以避免控制溢出。使用人工神经网络(ANN)作为平滑参数插值器,可以实时更新滤波器的参数,以便应对进给驱动系统的动态变化。我们已经在实际的进给驱动系统中验证了所提出策略的有效性和鲁棒性。
关键词 滚珠丝杠进给驱动系统变化高阶动态非同位控制模态特征修正器智能自适应调整算法    

The ball-screw feed drive has varying high-order dynamic characteristics due to flexibilities of the slender screw spindle and joints between components, and an obvious feature of non-collocated control when a direct position measurement using a linear scale is employed. The dynamic characteristics and non-collocated situation have long been the source of difficulties in motion and vibration control, and deteriorate the achieved accuracy of the axis motion. In this study, a dynamic model using a frequency-based substructure approach is established, considering the flexibilities and their variation. The position-dependent variation of the dynamic characteristics is then fully investigated. A corresponding control strategy, which is composed of a modal characteristic modifier (MCM) and an intelligent adaptive tuning algorithm (ATA), is then developed. The MCM utilizes a combination of peak filters and notch filters, thereby shaping the plant dynamics into a virtual collocated system and avoiding control spillover. An ATA using an artificial neural network (ANN) as a smooth parameter interpolator updates the parameters of the filters in real time in order to cope with the feed drive’s dynamic variation. Numerical verification of the effectiveness and robustness of the proposed strategy is shown for a real feed drive.

Keywords Ball-screw feed drives      Varying high-order dynamics      Non-collocated control      Modal characteristic modifier      Intelligent adaptive tuning algorithm     
最新录用日期:    在线预览日期:    发布日期: 2017-11-08
Hui Liu
Jun Zhang
Wanhua Zhao
Hui Liu,Jun Zhang,Wanhua Zhao. An Intelligent Non-Collocated Control Strategy for Ball-Screw Feed Drives with Dynamic Variations[J]. Engineering, 2017, 3(5): 641-647.
网址:     OR
Fig.1  Scheme of a 3M2S system. m1, m2, m3 are the three masses; k1 and k2 are the two springs; c1, c2, and cm2 are the dampings; x1, x2, and x3 are the displacements; and F1 is the force applied on m1.
Fig.2  FRFs of the 3M2S system. (a) h11; (b) h21; (c) h31.
Fig.3  Operating deflection shapes of the (a) rigid motion and (b) two resonant modes. θ1, θ2, and θ3 are the receptances of the three coordinates.
Fig.4  PD collocated control and its passive mechanical equivalence. kp: proportional gain; kd: derivative gain; r: given displacement.
Fig.5  Nyquist plots of collocated and non-collocated situations for 3M2S. v1/F1 and v2/F1 are the velocity receptances.
Fig.6  Collocated and non-collocated control in ball-screw feed drives.
Fig.7  (a) A general model considering the non-collocated situation and (b) its symbolic representation.
Fig.8  Three subsystems of a ball-screw feed drive.
Fig.9  Schematic model of the tri-subsystem receptance coupling via the screw-nut. Block “× d” stands for multiplication by the diameter of the ball screw.
Fig.10  Varying dynamics shown with families of magnitude plots (Ytable = 100–700 mm). (a) T1 in and θ1 out; (b) F3 in and θ1 out; (c) T1 in and x2 out; (d) F3 in and x2 out; (e) T1 in and x3 out; (f) F3 in and x3 out.
Fig.11  Varying dynamics h21 shown with cloud images (Ytable = 100–700 mm).
Fig.12  Resonant phase variation with table position (h21).
Fig.13  The proposed intelligent non-collocated control strategy. P: proportional; PI: proportional-integral.
Fig.14  Modifying effects of the proposed peak filter, where w/ variation refers to with variation.
Fig.15  The structure of the proposed ATA based on an ANN.
Mode Natural frequency (Hz) Damping ratio Phase(º)
1 49 0.120 –135
2 95 0.170 –155
3 130 0.090 –260
4 1030 0.003 –198
5 1529 0.010 –31
Tab.1  Modal characteristics identified for the test plant (Ytable= 115 mm).
Fig.16  Tracking responses and errors with PID control (Ytable = 115 mm), where w/ FFC refers to with feed-forward control and w/o FFC refers to without feed-forward control.
Fig.17  Tracking responses and errors with the proposed MCM control (Ytable = 115 mm).
Fig.18  An RMS errorcomparison.
1 Liu H, Lu D, Zhang J, Zhao W. Receptance coupling of multi-subsystem connected via a wedge mechanism with application in the position-dependent dynamics of ballscrew drives. J Sound Vib 2016;376:166–81
2 Chodavarapu PA, Spong MW. On noncollocated control of a single flexible lin k. In: Proceedings of the IEEE International Conference on Robotics and Automation; 1996 Apr 22–28; Minneapolis, USA. Piscataway: IEEE; 1996. p. 1101–6
3 Buhr C, Franchek MA, Bernhard RJ. Non-collocated adaptive-passive vibration control. J Sound Vib 1997;206(3):371–98
4 Kim SM, Oh JE. A modal filter approach to non-collocated vibration control of structures. J Sound Vib 2013;332(9):2207–21
5 Spector VA, Flashner H. Modeling and design implications of noncollocated control in flexible systems. J Dyn Sys Meas Control 1990;112(2):186–93
6 Wu S, Lian S, Chen S. Vibration control of a flexible beam driven by a ball-screw stage with adaptive notch filters and a line enhancer. J Sound Vib 2015;348:71–87
7 Mahmood IA, Moheimani SOR, Bhikkaji B. Precise tip positioning of a flexible manipulator using resonant control. IEEE/ASME Transactions Mechatronics 2008;13(2):180–6
8 Lee YS, Elliott SJ. Active position control of a flexible smart beam using internal model control. J Sound Vib 2001;242(5):767–91
9 Yang B, Mote CD. Active vibration control of the axially moving string in the S domain. J Appl Mech 1991;58(1):161–85
10 Torfs D, de Schutter J, Swevers J. Extended bandwidth zero phase error tracking control of non-minimal phase systems. J Dyn Sys Meas Control 1992;114(3):347–51
11 Han JH, Rew KH, Lee I. An experimental study of active vibration control of composite structures with a piezo-ceramic actuator and a piezo-film sensor. Smart Mater Struct 1997;6(5):549
12 Altintas Y, Verl A, Brecher C, Uriarte L, Pritschow G. Machine tool feed drives. CIRP Ann Manuf Technol 2011;60(2):779–96
13 Gordon DJ, Erkorkmaz K. Accurate control of ball screw drives using pole-placement vibration damping and a novel trajectory prefilter. Precis Eng 2013;37(2):308–22
14 Hanifzadegan M, Nagamune R. Tracking and structural vibration control of flexible ball-screw drives with dynamic variations. IEEE/ASME Transactions Mechatronics 2015;20(1):133–42
15 Zhou Y, Peng F, Li B. Adaptive notch filter control for the torsion vibration in lead-screw feed drive system based on neural network. In: Proceedings of the Intelligent Robotics and Applications, First International Conference, ICIRA 2008; 2008 Oct 15–17; Wuhan, China. Berlin: Springer; 2008. p. 803–12
16 Beauduin T, Fujimoto H, Terada Y. Adaptive vibration suppression perfect tracking control for linear time-varying systems with application to ball-screw feed drives. In: Proceedings of the International Workshop on Advanced Motion Control; 2016 Apr 22–24; Auckland, New Zealand. Piscataway: IEEE; 2016. p. 245–50
17 Itoh K, Iwasaki M, Matsui N. Robust fast and precise positioning of ball screw-driven table system on machine stand. In: Proceedings of the International Workshop on Advanced Motion Control; 2004 Mar 28; Kawasaki, Japan. Piscataway: IEEE; 2004. p. 511–5
18 Fernandez-Gauna B, Ansoategui I, Etxeberria-Agiriano I, Graña M. Reinforcement learning of ball screw feed drive controllers. Eng Appl Artif Intel 2014;30(1):107–17
19 Yabui S, Okuyama A, Atsumi T, Odai M. Development of optimized adaptive feed-forward cancellation with damping function for head positioning system in hard disk drives. J Adv Mech Design Sys Manuf 2013;7(1):39–51
20 He J, Fu ZF. Modal analysis . Oxford: Butterworth-Heinemann; 2001.
21 Imregun M, Ewins DJ. Complex modes — Origins and limits. In: Proceedings of the 13th International Modal Analysis Conference; 1995 Feb 13–16; Nashville, USA. Bellingham: SPIE Press; 1995. p. 2460.
[1] Zhuo Cheng, Lang Qin, Jonathan A. Fan, Liang-Shih Fan. New Insight into the Development of Oxygen Carrier Materials for Chemical Looping Systems[J]. Engineering, 2018, 4(3): 343-351.
[2] Jennifer A. Clark, Erik E. Santiso. Carbon Sequestration through CO2 Foam-Enhanced Oil Recovery: A Green Chemistry Perspective[J]. Engineering, 2018, 4(3): 336-342.
[3] Andrea Di Maria, Karel Van Acker. Turning Industrial Residues into Resources: An Environmental Impact Assessment of Goethite Valorization[J]. Engineering, 2018, 4(3): 421-429.
[4] Lance A. Davis. Falcon Heavy[J]. Engineering, 2018, 4(3): 300-.
[5] Augusta Maria Paci. A Research and Innovation Policy for Sustainable S&T: A Comment on the Essay ‘‘Exploring the Logic and Landscape of the Knowledge System”[J]. Engineering, 2018, 4(3): 306-308.
[6] Ning Duan. When Will Speed of Progress in Green Science and Technology Exceed that of Resource Exploitation and Pollutant Generation?[J]. Engineering, 2018, 4(3): 299-.
[7] Jian-guo Li, Kai Zhan. Intelligent Mining Technology for an Underground Metal Mine Based on Unmanned Equipment[J]. Engineering, 2018, 4(3): 381-391.
[8] Veena Sahajwalla. Green Processes: Transforming Waste into Valuable Resources[J]. Engineering, 2018, 4(3): 309-310.
[9] Junye Wang, Hualin Wang, Yi Fan. Techno-Economic Challenges of Fuel Cell Commercialization[J]. Engineering, 2018, 4(3): 352-360.
[10] Raymond RedCorn, Samira Fatemi, Abigail S. Engelberth. Comparing End-Use Potential for Industrial Food-Waste Sources[J]. Engineering, 2018, 4(3): 371-380.
[11] Ning Duan, Linhua Jiang, Fuyuan Xu, Ge Zhang. A Non-Contact Original-State Online Real-Time Monitoring Method for Complex Liquids in Industrial Processes[J]. Engineering, 2018, 4(3): 392-397.
[12] Keith E. Gubbins, Kai Gu, Liangliang Huang, Yun Long, J. Matthew Mansell, Erik E. Santiso, Kaihang Shi, Małgorzata Ś liwińska-Bartkowiak, Deepti Srivastava. Surface-Driven High-Pressure Processing[J]. Engineering, 2018, 4(3): 311-320.
[13] Steff Van Loy, Koen Binnemans, Tom Van Gerven. Mechanochemical-Assisted Leaching of Lamp Phosphors: A Green Engineering Approach for Rare-Earth Recovery[J]. Engineering, 2018, 4(3): 398-405.
[14] Robert S. Weber, Johnathan E. Holladay. Modularized Production of Value-Added Products and Fuels from Distributed Waste Carbon-Rich Feedstocks[J]. Engineering, 2018, 4(3): 330-335.
[15] Hualin Wang, Pengbo Fu, Jianping Li, Yuan Huang, Ying Zhao, Lai Jiang, Xiangchen Fang, Tao Yang, Zhaohui Huang, Cheng Huang. Separation-and-Recovery Technology for Organic Waste Liquid with a High Concentration of Inorganic Particles[J]. Engineering, 2018, 4(3): 406-415.
Full text



国内刊号:CN10-1244/N    国际刊号:ISSN2095-8099
版权所有 © 2015 高等教育出版社  《中国工程科学》杂志社