Hostname: page-component-76fb5796d-zzh7m Total loading time: 0 Render date: 2024-04-26T23:42:28.413Z Has data issue: false hasContentIssue false
  • English
  • Français

Digital platform-based multi-domain virtual prototype simulation on a high-speed parallel manipulator

Published online by Cambridge University Press:  05 October 2011

Yang Zhiyong ,
Feng Wenhao ,
Wu Jiang  and
Huang Tian
Yang Zhiyong*
Affiliation:
School of Mechanical Engineering, Tianjin University, Tianjin 300072, China
Feng Wenhao
Affiliation:
School of Mechanical Engineering, Tianjin University, Tianjin 300072, China
Wu Jiang
Affiliation:
School of Mechanical Engineering, Tianjin University, Tianjin 300072, China
Huang Tian
Affiliation:
School of Mechanical Engineering, Tianjin University, Tianjin 300072, China
*
*Corresponding author. E-mail: meyang@tju.edu.cn
Get access Rights & Permissions [Opens in a new window]

Summary

This paper presents how to build an all-digital co-simulation platform of a mechtronic system so as to reduce the burden and error of system modeling. In the construction of a platform, a driving system, including a motor, a pulse-width modulation (PWM) and a controller, is simulated using Matlab/Simulink. The behavior of the mechanism is analyzed using the ADAMS software. By the proper interface function for the real-time communication between two parts of the models, a virtual working environment is established. Finally, a proportional integral derivative (PID) controller verifies the validity of the digital platform.

Keywords

Virtual prototypeMechtronicMulti-domain simulationParallel manipulator
Type
Articles
Information
Robotica , Volume 30 , Issue 5 , September 2012 , pp. 827 - 835
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.Koren, Y., “Reconfigurable manufacturing systems,” (keynote paper) CIRP Annu. 49, 527–540 (2000).Google Scholar
2.Cheng, H., Yiu, Y. K. and Li, Z. X., “Dynamics and control of redundantly actuated parallel manipulators,” IEEE/ASME Trans. Mechatronics 8, 483–491 (2003).CrossRefGoogle Scholar
3.Codourey, A. and Yoshikawa, T., “Dynamic Modelling and Mass Matrix Evaluation of the DELTA Parallel Robot for Axes Decoupling Control,” In: Proceedings of the 1996 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '96), Osaka, Japan, vol. 3 (Nov. 4–8, 1996) pp. 1211–1218.Google Scholar
4.Lin, F. J. and Wai, R. J., “A hybrid computed torque controller using fuzzy neural network for motor-quick-return servo mechanism,” IEEE/ASME Trans. Mechatronics 6, 75–89 (2001).Google Scholar
5.Krause, P. C., Analysis of Electric Machinery (McGraw, New York, USA, 1986).Google Scholar
6.Timár, A., Bognár, G., Poppe, A. and Rencz, M., “Electro-Thermal Co-simulation of ICs with Runtime Back-Annotation Capability,” Proceedings of the 16th Therminic Workshop, Barcelona, Spain, (Oct. 6–8, 2010).Google Scholar
7.Zhang, D. X., Zeng, X. H., Wang, P. Y. and Wang, Q. N., “Co-simulation with AMESim and MATLAB for Differential Dynamic Coupling of Hybrid Electric Vehicle,” In: Proceedings of IEEE Intelligent Vehicles Symposium, Xi'an, China (Jun. 3–5, 2009) pp. 761–765.Google Scholar
8.Zhu, D. L., Qin, J. Y., Zhang, Y., Zhang, H. and Xia, M. M., “Research on Co-Simulation Using ADAMS and MATLAB for Active Vibration Isolation System,” Proceedings of 2010 International Conference on Intelligent Computation Technology and Automation, Changsha, China (May 11–12, 2010).Google Scholar
9.Kerttula, M., Salmela, M. and Heikkinen, M., “Virtual Reality Prototyping—A Framework for the Development of Electronics and Telecommunication Products,” In: Proceedings of the Eighth International Workshop on Rapid System Prototyping (Cat. No.97TB100155) (IEEE Computer Society, Washington, DC, USA, 1997) pp. 2–11.Google Scholar
10.Cui, H. L., Zhu, Z. Q., Gan, Z. X. and Brogardh, T., “Kinematic analysis and error modeling of TAU parallel robot,” Robot. Comput.-Integr. Manuf. 21 (6), 497–505 (2005).CrossRefGoogle Scholar
11.Klaassen, B., Kirchner, F. and Spenneberg, D., “Integration of Robot Control Programs into ADAMSTM, Including Sensor Feedback,” In: Proceedings of the 14th European Simulation Multiconference, Ghent, Belgium (May 23–26, 2000) pp. 259–262.Google Scholar
12.Mohammed, O. A., Liu, S. and Liu, Z., “Phase-variable model of PM synchronous machines for integrated motor drives,” IEE Proc. Sci. Meas. Tech. 151 (6), 423–429 (2004).CrossRefGoogle Scholar
13.Choi, S. H. and Chan, A. M. M., “A virtual prototyping system for rapid product development,” Comput. Aided Des. 36 (5), 401–412 (2004).CrossRefGoogle Scholar
14.Tomi, M., Kelervo, N. and Rauno, H., “A 3D model-based control of an excavator,” Autom. Constr. 15 (5), 571–577 (2006).Google Scholar
15.Yang, Z. Y., Huang, T., Mei, J. P. and Wu, J., “Whole workspace optimization based parameter tuning of high-speed parallel manipulator controller,” Chin. J. Mech. Eng. 42 (9), 123–129 (2006) (in Chinese).CrossRefGoogle Scholar
16.Yang, Z. Y. and Huang, T., “A new method for tuning PID parameters of a 3-DoF reconfigurable parallel kinematic machine” Proc. IEEE Robot. Autom. 3, 2249–2254 (2004).Google Scholar
17.Huang, T., Planar Parallel Robot Mechanism with Two Translational Degrees of Freedom. US Patent No. US7090458 B2 (2006.08.15) (US Patent Office, Alexandria, VA, 2006).Google Scholar
18.Huang, T., Mei, J. P. and Li, Z. X., “A method for estimating servomotor parameters of a parallel robot for rapid pick-and-place operations,” J. Mech. Des. Trans. ASME 127 (4)596–601 (2005).CrossRefGoogle Scholar