Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-10T17:35:22.185Z Has data issue: false hasContentIssue false
  • English
  • Français

Driving force analysis for the secondary adjustable system in FAST

Published online by Cambridge University Press:  22 February 2011

Zhu-Feng Shao ,
Xiaoqiang Tang ,
Xu Chen  and
Li-Ping Wang
Zhu-Feng Shao
Affiliation:
Institute of Manufacturing Engineering, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, P.R. China
Xiaoqiang Tang*
Affiliation:
Institute of Manufacturing Engineering, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, P.R. China
Xu Chen
Affiliation:
Institute of Manufacturing Engineering, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, P.R. China
Li-Ping Wang
Affiliation:
Institute of Manufacturing Engineering, Department of Precision Instruments and Mechanology, Tsinghua University, Beijing 100084, P.R. China
*
*Corresponding author. E-mail: tang-xq@mail.tsinghua.edu.cn
Get access Rights & Permissions [Opens in a new window]

Summary

The Secondary Adjustable System (SAS) addressed here is a central component of the Five-hundred-meter Aperture Spherical radio Telescope (FAST). It is a 6-degree-of-freedom rigid Stewart manipulator, in which one platform (the end-effector) should be controlled to track-desired trajectory when another platform (denoted as the base) is moving. Driving force analysis of the SAS is the basis for selecting rational servomotors and guaranteeing the dynamic performance, which will affect the terminal pose accuracy of the FAST. In order to determine the driving forces of the SAS, using the Newton–Euler method, the inverse dynamics of the Stewart manipulator is modeled by considering the motion of the base. Compared with the traditional dynamic models, the inverse dynamic model introduced here possesses an inherent wider application range. By adopting the kinematic and dynamic parameters of the FAST prototype, the driving force analysis of the SAS is carried out, and the driving force optimization strategies are proposed. Calculation and analysis presented in the paper reveal that there are three main factors affecting the driving forces of the SAS. In addition, the driving force analysis of this paper lays out guidelines for the design and control of the FAST prototype, as well as the structure and trajectory optimization.

Keywords

Newton–Euler methodStewart manipulatorInverse dynamicsInverse kinematicsFAST
Type
Articles
Information
Robotica , Volume 29 , Issue 6 , October 2011 , pp. 903 - 915
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Nan, R. and Peng, B., “A Chinese concept for the 1-km 2-radio telescope,” Acta Astronaut. 46 (10–12), 667–675 (2000).CrossRefGoogle Scholar
2.Nan, R., “Five hundred meter aperture spherical radio telescope (FAST),” Sci. China: Series G Phys. Mech. & Astron. 49 (2), 129–148 (2006).Google Scholar
3.Sharon, A., The Macro/Micro Manipulator: An Improved Architecture for Robot Control, Ph.D. Thesis (Massachusetts, USA: Massachusetts Institute of Technology, 1988).Google Scholar
4.Lin, J., “Computer-aided symbolic dynamic modeling for Stewart-platform manipulator,” Robotica 27 (3), 331–341 (2009).CrossRefGoogle Scholar
5.Lee, S.-H., Song, J.-B., Choi, W.-C. and Hong, D., “Position control of a Stewart platform using inverse dynamics control with approximate dynamics,” Mechatronics 13 (6), 605–619 (2003).CrossRefGoogle Scholar
6.Wu, J., Wang, J., Wang, L. and Li, T., “Dynamics and control of a planar 3-DOF parallel manipulator with actuation redundancy,” Mech. Mach. Theory 44 (4), 835–849 (2009).CrossRefGoogle Scholar
7.Wu, D. S. and Gu, H. B., “Adaptive sliding control of six-DOF flight simulator motion platform,” Chin. J. Aeronaut. 20 (5), 425–433 (2007).Google Scholar
8.Dasgupta, B. and Mruthyunjaya, T. S., “The Stewart manipulator: A review,” Mech. Mach. Theory 35 (2), 15–40 (2000).CrossRefGoogle Scholar
9.Mahboubkhah, M., Nategh, M. J. and Khadem, S. E., “Vibration analysis of Machine tool's hexapod table,” Int. J. Adv. Manuf. Technol. 38 (11–12), 1236–1243 (2008).CrossRefGoogle Scholar
10.Wang, J., Li, T. and Duan, G., “Research and development in the field of parallel kinematic machines” (in Chinese), Eng. Sci. 4 (6), 63–70 (2002).Google Scholar
11.Liu, X.-J. and Bonev, L. A., “Orientation capability, error analysis, and dimensional optimization of two articulated tool heads with parallel kinematics,” J. Manuf. Sci. Eng. – Trans. ASME 130 (1), 110151–110159 (2008).CrossRefGoogle Scholar
12.Hanieh, A. A., Active Isolation and Damping of Vibration via Stewart Platform, Ph.D. Thesis (Belgium: ULB University, 2003).Google Scholar
13.Zheng, G. and Leonard, S. H., “Six-degree-of-freedom active vibration isolation using a Stewart platform mechanism,” J. Robot. Syst. 5 (10), 725–744 (1993).Google Scholar
14.Do, W. Q. D. and Yang, D. C. H., “Inverse dynamic analysis and simulation of a platform type of robot,” J. Robot. Syst. 5 (3), 209–227 (1988).CrossRefGoogle Scholar
15.Ji, Z., “Study of the Effect of Leg Inertia in Stewart Platforms,” Proceedings of the 1993 IEEE International Conference on Robotics and Automation, Atlanta, Georgia, USA (May 2–6, 1993) pp. 121–126.Google Scholar
16.Dasgupta, B. and Mruthyunjaya, T. S., “Closed-from dynamic equations of the general Stewart platform through the Newton–Euler approach,” Mech. Mach. Theory 33 (7), 993–1012 (1998).CrossRefGoogle Scholar
17.Hong, J. and Yamamoto, M., “A calculation method of the reaction force and moment for a Delta-type parallel link robot fixed with a frame,” Robotica 27 (4), 579–587 (2009).CrossRefGoogle Scholar
18.Li, Y. and Xu, Q., “Kinematics and inverse dynamics analysis for a general 3-PRS spatial parallel mechanism,” Robotica 23 (2), 219–229 (2005).CrossRefGoogle Scholar
19.Wang, J. and Gosselin, C. M., “A new approach for the dynamic analysis of parallel manipulators,” Multibody Syst. Dyn. 2 (3), 317–334 (1998).CrossRefGoogle Scholar
20.Abdellatif, H. and Heimann, B., “Computational efficient inverse dynamics of 6-DOF fully parallel manipulators by using the Lagrangian formalism,” Mech. Mach. Theory 44 (1), 192–207 (2009).CrossRefGoogle Scholar
21.Staicu, S., Liu, X.-J. and Wang, J., “Inverse dynamics of the HALF parallel manipulator with revolute actuators,” Nonlinear Dyn. 50 (1–2), 1–12 (2007).CrossRefGoogle Scholar
22.Staicu, S., Liu, X.-J. and Li, J., “Explicit dynamics equations of the constrained robotic systems,” Nonlinear Dyn. 58 (1–2), 217–235 (2009).CrossRefGoogle Scholar
23.Shao, Z., Tang, X., Chen, X. and Wang, L., “Inertia match research of a 3-RRR reconfigurable planar parallel manipulator,” Chin. J. Mech. Eng. 22 (3), 1–9 (2009).CrossRefGoogle Scholar
24.Staicu, S., “Recursive modelling in dynamics of Delta parallel robot,” Robotica 27 (2), 199–207 (2009).CrossRefGoogle Scholar
25.Koekebakker, S., Model Based Control of a Flight Simulator Motion System, Ph.D. Thesis (Delft, Netherlands: Delft University of Technology, 2001)Google Scholar
26.Yuan, Y. and Li, Y., “Multi-Degree of Freedom Vibration Model for a 3-DOF Hybrid Robot,” Proceedings of 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Singapore (July 14–17, 2009).Google Scholar