Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-23T21:55:01.629Z Has data issue: false hasContentIssue false
  • English
  • Français

Dimensional optimization of the Stewart platform based on inertia decoupling characteristic

Published online by Cambridge University Press:  08 August 2014

Zhihua Liu ,
Xiaoqiang Tang ,
Zhufeng Shao  and
Liping Wang
Zhihua Liu
Affiliation:
Department of Mechanical Engineering, The State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
Xiaoqiang Tang*
Affiliation:
Department of Mechanical Engineering, The State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
Zhufeng Shao
Affiliation:
Department of Mechanical Engineering, The State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
Liping Wang
Affiliation:
Department of Mechanical Engineering, The State Key Laboratory of Tribology, Tsinghua University, Beijing 100084, China
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

Inertia strongly influences the dynamic performance of parallel manipulators, and ignorance of inertia is apt to result in negative phenomena such as vibrations, overshoot, and slow response. This study analyzes the inertia-decoupling characteristic of Stewart platform. Because the inertia matrix of the Stewart platform is usually non-diagonal, inertia coupling occurs between its legs. Herein, decoupling to inertia is implemented, and independent control channels are determined. The influence of decoupled inertia on the control system is analyzed using the Adams simulation software, and the inertia index of the Stewart platform is proposed. Experiments are conducted on a prototype of the Stewart platform to verify the eigenvalue characteristic of decoupled inertia. The distribution of inertia index in the operational workspace is provided, and the influence of dimensional parameters on inertia index is discussed. Finally, dimensional optimization is realized with a set of optimized dimensions for good dynamic performance.

Keywords

Inertia matrixDecouplingEigenvalueParallel manipulator
Type
Articles
Information
Robotica , Volume 34 , Issue 5: RAAD , May 2016 , pp. 1151 - 1167
Copyright
Copyright © Cambridge University Press 2014 

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.Cao, Y., Gosselin, C., Ren, P. and Zhou, H., “Orientation ability analyses of a special class of the Stewart-Gough parallel manipulators using the unit quaternion representation,” Adv. Robot. 27 (2), 147–158 (2013).Google Scholar
2.Wang, D., Fan, R. and Chen, W., “Performance enhancement of a three-degree-of-freedom parallel tool head via actuation redundancy,” Mech. Mach. Theory 71, 142–162 (2014).Google Scholar
3.Xie, F., Liu, X. J., You, Z. and Wang, J., “Type synthesis of 2T1R-type parallel kinematic mechanisms and the application in manufacturing,” Robot. Comput. Integr. Manuf. 30 (1), 1–10 (2014).Google Scholar
4.Tang, X., Zhu, W., Sun, C. and Yao, R., “Similarity model of feed support system for FAST,” Exp. Astron. 29 (3), 177–187 (2011).Google Scholar
5.Shao, Z. F., Tang, X., Chen, X. and Wang, L. P., “Driving force analysis for the secondary adjustable system in FAST,” Robotica 29 (6), 903–915 (2011).CrossRefGoogle Scholar
6.Yu, D., Li, H. and Chen, W., “Kinematic calibration of parallel robots for docking mechanism motion simulation,” Int. J. Adv. Robot. Syst. 8 (4), 158–165 (2011).Google Scholar
7.Xiong, H., Huang, Q., Ma, J. and Han, J., “Research on Co-Modeling Virtual Prototype of Motion System of Flight Simulator,” Proceedings of IEEE International Conference on Mechatronics and Automation, 2009 (ICMA 2009) (IEEE, Washington, DC, 2009, Aug.) pp. 2260–2264.Google Scholar
8.Dasgupta, B. and Mruthyunjaya, T. S., “Closed-form dynamic equations of the general Stewart platform through the Newton–Euler approach,” Mech. Mach. Theory 33 (7), 993–1012 (1998).Google Scholar
9.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
10.Tsai, L. W., “Solving the inverse dynamics of a Stewart–Gough manipulator by the principle of virtual work,” J. Mech. Des. 122, 3 (2000).Google Scholar
11.Yun, Y. and Li, Y. “Multi-Degree of Freedom Vibration Model for a 3-DOF Hybrid Robot,” Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2009 (AIM 2009) (IEEE, Washington, DC, 2009, Jul.) pp. 1474–1479.Google Scholar
12.Lopes, A. M., “Complete dynamic modelling of a moving base 6-dof parallel manipulator,” Robotica 28 (5), 781–793 (2010).CrossRefGoogle Scholar
13.Ting, Y., Chen, Y. S. and Wang, S. M., “Task-Space Control Algorithm for Stewart Platform,” Proceedings of the 38th IEEE Conference on Decision and Control, vol. 4 (IEEE, Washington, DC, 1999) pp. 3857–3862.Google Scholar
14.Shang, W., Cong, S. and Ge, Y., “Coordination motion control in the task space for parallel manipulators with actuation redundancy,” IEEE Trans. Autom. Sci. Eng. 10 (3), 665–673 (2013).Google Scholar
15.Yang, C., Huang, Q., Jiang, H., Peter, O. Ogbobe and Han, J., “PD control with gravity compensation for hydraulic 6-DOF parallel manipulator,” Mech. Mach. Theory 45 (4), 666–677 (2010).Google Scholar
16.Kim, D. H., Kang, J. Y. and Lee, K. I., “Robust tracking control design for a 6-DOF parallel manipulator,” J. Robot. Syst. 17 (10), 527–547 (2000).Google Scholar
17.Su, Y. X., Duan, B. Y. and Zheng, C. H., “Nonlinear PID control of a six-DOF parallel manipulator,” IEEE Proc.,Control Theory Appl. 151 (1), 95–102 (2004).Google Scholar
18.Jian, X., Zhiyong, T., Zhongcai, P., Shao, H. and Lanbo, L., “Adaptive controller for 6-DOF parallel robot using TS fuzzy inference,” Int. J. Adv. Robot. Syst. 10, 1–9 (2013).Google Scholar
19.Liu, Y., Jia, X., Han, J. and Zhao, X., “A Robust Adaptive Fuzzy Sliding Mode Control Method of 3-RRRT Parallel Manipulator,” Proceedings of the IEEE International Conference on Automation and Logistics, 2009 (ICAL '09) (IEEE, Washington, DC, 2009, Aug.) pp. 1883–1887.CrossRefGoogle Scholar
20.Huang, T., Mei, J., Li, Z., Zhao, X. and Chetwynd, D. G., “A method for estimating servomotor parameters of a parallel robot for rapid pick-and-place operations,” J. Mech. Des. 127, 596–601 (2005).Google Scholar
21.Chen, Y. and McInroy, J. E., “Decoupled control of flexure-jointed hexapods using estimated joint-space mass-inertia matrix,” IEEE Trans. Control Syst. Technol. 12 (3), 413–421 (2004).Google Scholar
22.Shao, Z., Tang, X., Chen, X. and Wang, L., “Inertia matching of a 3-RRR reconfigurable planar parallel manipulator,” Chin. J. Mech. Eng. 22 (6), 791–799 (2009).Google Scholar
23.Shao, Z., Tang, X., Chen, X. and Wang, L., “Research on the inertia matching of the Stewart parallel manipulator,” Robot. Comput.-Integr. Manuf. 28 (6), 649–659 (2012).Google Scholar
24.Ogbobe, P., Zhengmao, Y., Hougzhou, J. and Junwei, H., “Analytical Formulation of Coupling Effects Matrix Between Degrees of Freedom Motion of Parallel Robots,” Proceedings of the IEEE International Conference on Intelligent Computation Technology and Automation (ICICTA 2010), vol. 1 (2010, May), pp. 711–714.CrossRefGoogle Scholar
25.Yao, Y., Fu, S. and Han, L., “Block diagonal dominance analysis and judgment of Stewart platform's joint-space inertia matrix,” Chin. J. Mech. Eng. 44 (6), 101–106 (2008).Google Scholar