International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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On the Voltage-Based Control of Robot Manipulators

  • Fateh, Mohammad Mehdi (Department of Electrical and Robotic Engineering, Shahrood University of Technology)
  • Published : 2008.10.31
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Abstract

This paper presents a novel approach for controlling electrically driven robot manipulators based on voltage control. The voltage-based control is preferred comparing to torque-based control. This approach is robust in the presence of manipulator uncertainties since it is free of the manipulator model. The control law is very simple, fast response, efficient, robust, and can be used for high-speed tracking purposes. The feedback linearization is applied on the electrical equations of the dc motors to cancel the current terms which transfer all manipulator dynamics to the electrical circuit of motor. The control system is simulated for position control of the PUMA 560 robot driven by permanent magnet dc motors.

Keywords

References

  1. C. An, C. Atkeson, and J. Hollerbach, Model Based Control of a Robot Manipulator, MIT Press, Cambridge, MA, 1988
  2. Z. Schiller, "Time-energy optimal control of articulated systems with geometric path constraints," Journal of Dynamic Systems, Measurement and Control, Trans. ASME, vol. 118, pp. 139-143, 1996 https://doi.org/10.1115/1.2801134
  3. S. Torres, J. A. Mendez, L. Acosta, and V. M. Becerra, "On improving the performance in robust controllers for robot manipulators with parametric disturbances," Control Engineering Practice, vol. 15, pp. 557-566, 2007 https://doi.org/10.1016/j.conengprac.2006.10.003
  4. M. W. Spong, "On the robust control of robot manipulators," IEEE Trans. on Automatic Control, vol. 37, no. 11, pp. 1782-1786, November 1992 https://doi.org/10.1109/9.173151
  5. C. S. Chiu, K. Y. Lian, and T. C. Wu, "Robust adaptive motion/force tracking control design for uncertain constrained robot manipulators," Automatica, vol. 40, pp. 2111-2119, 2004
  6. Y. Tang, F. Sun, and Z. Sun, "Neural network control of flexible-link manipulators using sliding mode," Neurocomputing, vol. 70, pp. 288-295, 2006 https://doi.org/10.1016/j.neucom.2006.01.030
  7. L. Tian and C. Collins, "Adaptive neuro-fuzzy control of a flexible manipulator," Mechatronics, vol. 15, pp. 1305-1320, 2005 https://doi.org/10.1016/j.mechatronics.2005.02.001
  8. Y. Li, "Robust neural networks compensating motion control of reconfigurable manipulator," Proc. of the First Int. Conf. on Innovative Computing, Information and Control, vol. 2, pp. 388-391, 2006
  9. S. Purwar, I. N. Kar, and A. N. Jha, "Adaptive control of robot manipulators using fuzzy logic systems under actuator constraints," Fuzzy Sets and Systems, vol. 152, pp. 651-664, 2005 https://doi.org/10.1016/j.fss.2004.11.012
  10. C. Liu, C. C. Cheah, and J. J. E. Slotine, "Adaptive Jacobian tracking control of rigid-link electrically driven robots based on visual taskspace information," Automatica, vol. 42, pp. 1491-1501, 2006 https://doi.org/10.1016/j.automatica.2006.04.022
  11. M. W. Spong, Motion Control of Robot Manipulators, in Handbook of Control, W. Levine, editor, CRC Press, pp. 1339-1350, 1996
  12. J. V. Miro and A. S. White, "Modelling an industrial manipulator a case study," Simulation Practice and Theory, vol. 9, pp. 293-319, 2002 https://doi.org/10.1016/S0928-4869(01)00046-5
  13. F. Reyes and R. Kelly, "Experimental evaluation of model-based controllers on a direct-drive robot arm," Mechatronics, vol. 11, pp. 267-282, 2001 https://doi.org/10.1016/S0957-4158(00)00008-8
  14. M. W. Spong and M. Vidyasagar, Robot Dynamics and Control, John Wiley and Sons, Inc, 1989
  15. R. Kelly, V. Santibiflez, and H. Berghuis, "Pointto- point robot control under actuator constraints," Control Engineering Practice, vol. 5, no. l, pp. 1555-1562, 1997 https://doi.org/10.1016/S0967-0661(97)10009-0
  16. T. J. Tarn, A. K. Bejczy, G. T. Marth, and A. K. Ramadorai, "Performance comparison of four manipulator servo schemes," IEEE Control Systems Magazine, vol. 13, no. 1, pp. 22-29, Feb. 1993 https://doi.org/10.1109/37.184789
  17. M. B. JR Leahy, and G. N. Saridis, "Compensation of industrial manipulator dynamics," The International Journal of Robotics Research, vol. 8, no. 4, pp. 73-84, 1989 https://doi.org/10.1177/027836498900800404
  18. P. Chiacchio, F. Pierrot, L. Sciavicco, and B. Siciliano, "Robust design of independent joint controllers with experimentation on a high-speed parallel robot," IEEE Trans. on Industrial Electronics, vol. 40, pp. 393-403, 1993 https://doi.org/10.1109/41.232228
  19. L. L. Chang and C. C. Chuan, "Rigid modelbased fuzzy control of flexible-joint manipulators," Journal of Intelligent and Robotic Systems, vol. 13, pp. 107-126, 1995 https://doi.org/10.1007/BF01254847
  20. L. C. Lin and T. E. Lee, "Integrated PID-type learning and fuzzy control for flexible-joint manipulators," Journal of Intelligent and Robotic Systems, vol. 18, no. 1, pp. 47-66, 1997 https://doi.org/10.1023/A:1007942528058
  21. J. J. Craig, Introduction to Robotics, Mechanics and Control, Addison-Wesley, 1989
  22. P. I. Corke and B. Armstrong-Hlouvry, "A search for consensus among model parameters reported for the PUMA 560 robot," Proc. IEEE Int. Conf. Robotics and Automation, vol. 1, pp. 1608-1613, San Diego, 1994
  23. G. F. Wyeth, J. Kennedy, and J. Lillywhite, "Distributed digital control of a robot arm," Proc. of the Australian Conf. on Robotics and Automation," Melbourne, pp. 217-222, August 30 - September 1, 2000
  24. P. I. Corke, "Robotics toolbox for MATLAB," IEEE Robotics & Automation Magazine, vol. 3, no. 1, pp. 24-32, 1996 https://doi.org/10.1109/100.486658