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A stable adaptive force/position controller for a C5 parallel robot: a neural network approach

Published online by Cambridge University Press:  17 January 2012

B. Achili ,
B. Daachi ,
Y. Amirat ,
A. Ali-Cherif  and
M. E. Daâchi
B. Achili*
Affiliation:
Computer Science Lab., LIASD-University of Paris 8, 2, rue de la liberté, 93526 Saint Denis Cedex, France
B. Daachi
Affiliation:
Images, Signals and Intelligent Systems Lab. (LISSI), University of Paris East Créteil 12, 120-122, rue Paul Armangot, 94400 Vitry/Seine, France
Y. Amirat
Affiliation:
Images, Signals and Intelligent Systems Lab. (LISSI), University of Paris East Créteil 12, 120-122, rue Paul Armangot, 94400 Vitry/Seine, France
A. Ali-Cherif
Affiliation:
Computer Science Lab., LIASD-University of Paris 8, 2, rue de la liberté, 93526 Saint Denis Cedex, France
M. E. Daâchi
Affiliation:
Department of Electronics, University of Sétif, Algeria
*
*Corresponding author. E-mail: [email protected]
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Summary

This paper presents an adaptive force/position controller for a parallel robot executing constrained motions. This controller, based on an MLPNN (or Multi-Layer Perceptron Neural Network), does not require the inverse dynamic model of the robot to derive the control law. A neural identification of the dynamic model of the robot is proposed to determine the principal components of the MLPNN input vector. The latter is used to compensate the dynamic effects arising from the robot–environment interaction and its parameters are adjusted according to an adaptation law based on the Lyapunov-analysis methodology. The proposed controller is evaluated experimentally on the C5 parallel robot. This method is capable of tracking accurately the force/position trajectories and its stability robustness is proved.

Keywords

Adaptive controlNeural networkStability analysisParallel robot
Type
Articles
Information
Robotica , Volume 30 , Issue 7 , December 2012 , pp. 1177 - 1187
Copyright
Copyright © Cambridge University Press 2012

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References

1. Achili, B., Daachi, B., Amirat, Y. and Ali-Cherif, A., “A robust adaptive control of a parallel robot,” Int. J. Control 83 (10), 2107–2119 (2010).CrossRefGoogle Scholar
2. Daachi, B., Madani, T. and Benallegue, A., “Adaptive neural controller for redundant robot manipulators and collision avoidance with mobile obstacles,” Neurocomputing 79, 50–60 (Mar. 1, 2012).CrossRefGoogle Scholar
3. Kilicaslan, S., Ozgoren, M. K. and Ider, S. K., “Hybrid force and motion control of robots with flexible links,” Mech. Mach. Theory 45 (1), 91–105 (2010).CrossRefGoogle Scholar
4. Visioli, A., Ziliani, G., Legnani, G. and Ozgoren, S., “Iterative-learning hybrid force/velocity control for contour tracking,” IEEE Trans. Robot. 26 (2) 388–393 (2010).CrossRefGoogle Scholar
5. Farooq, M., Daobo, D. W. and Dar, N., “Improved hybrid position/force controller design of a flexible robot manipulator using a sliding observer,” J. Syst. Eng. Electron. 20 (1), 146–158 (2009).Google Scholar
6. Karayiannidis, Y. and Doulgeri, Z., “Adaptive control of robot contact tasks with on-line learning of planar surfaces,” Automatica 45 (10), 2374–2382 (2009).CrossRefGoogle Scholar
7. Achili, B., Daachi, B., Ali-Cherif, A. and Amirat, Y., “Robust Neural Adaptive Force Controller for a C5 Parallel Robot,” Proceedings of the IEEE-ICAR (International Conference on Advanced Robotics), Munich, Germany (June 2009) pp. 1–6.Google Scholar
8. 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
9. Touati, Y., Amirat, Y., Saadia, N. and Ali-Chérif, A., “A neural network-based approach for an assembly cell control,” Appl. Soft Comput. 8 (4), 1335–1343 (2008).CrossRefGoogle Scholar
10. Wei, M., Bai, B., Sung, A. H., Liu, Q., Wang, J. and Cather, M. E., “Predicting injection profiles using ANFIS,” Inform. Sci. 177, 4445–4461 (2007).CrossRefGoogle Scholar
11. Ziliani, G., Visioli, A. and Legnani, G., “Gain scheduling for hybrid force/velocity control in contour tracking task,” Int. J. Adv. Robot. Syst. 3 (4), 367–374 (2006).CrossRefGoogle Scholar
12. Graham, A. E., Xie, S. Q., Aw, K. C., Xu, W. L., and Mukherjee, S., “Design of a Parallel Long Bone Fracture Reduction Robot with Planning Treatment Tool,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, China (Oct. 9–15, 2006) pp. 1255–1260.Google Scholar
13. Daachi, B. and Benallegue, A., “A neural network adaptive controller for end-effector tracking of redundant robot manipulators,” J. Intell. Robot. Syst. 46 (3), 245–262 (2006).CrossRefGoogle Scholar
14. Temei, L., Qingguo, L. and Payendeh, S., “NN-Based Solution of Forward Kinematics of 3DOF Parallel Spherical Manipulator,” Proceedings of the IEEE/RSJ International Conference Intelligent Robots and Systems (2005) pp. 1344–1349.Google Scholar
15. Bailly, Y. and Amirat, Y., “Modeling and Control of a Hybrid Continum Active Catheter for Aortic Aneurysm Treatment,” Proceedings of the IEEE International Conference on Robotics and Automation, Barcelona, Spain (Apr. 18–22, 2005) pp. 924–929.CrossRefGoogle Scholar
16. Khalil, W. and Ibrahim, O., “General Solution for the Dynamic Modeling of Parallel Robots,” Proceedings of the International Conference on Robotics and Automation, New Orleans, Louisiana (Apr. 26–May 1, 2004) pp. 3665–3670.Google Scholar
17. Maurin, B., Gangloff, J., Bayle, B., Mathelin, M., Piccin, O., Zanne, P., Doignon, C., Soler, L. and Gangi, A., “A Parallel Robotic System with Force Sensors for Percutaneous Procedure Under CT-Guidance,” In: Medical Image Computing and Computer-Assisted Intervention (MICCAI), Lecture Notes in Computer Science, Saint-Malo, France, vol. 3217, (Oct. 2004), pp. 176–183.Google Scholar
18. Chian, C. S., Lian, K. Y. and Wu, T. C., “Robust adaptive motion/force tracking control design for uncertain constrained robot manipulators,” Automatica 40 (12), 2111–2119 (2004).Google Scholar
19. Cheah, C. C., Kawamura, S. and Arimoto, S., “Stability of hybrid position and force control for robotic manipulator with kinematics and dynamics uncertainties,” Automatica 39 (5), 847–855 (2003).CrossRefGoogle Scholar
20. Shoham, M., Burman, M., Zehavi, E., Joskowicz, L., Batkilin, E. and Kunicher, Y., “Bone-mounted miniature robot for surgical procedures: Concept and clinical applications,” IEEE Trans. Robot. Autom. 19 (5), 893–901 (2003).CrossRefGoogle Scholar
21. Merlet, J. P., “Optimal Design for the Micro Parallel Robot Mips,”. Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC, USA (May 11–15, 2002) pp. 1149–1154.Google Scholar
22. Khalil, W. and Dombre, E., Modeling, Identification and Control of Robots (Hermès Penton Ltd., London, UK, 2002).Google Scholar
23. Daachi, B., Benallegue, A. and M'Sirdi, N. K., “A Stable Neural Adaptive Force Controller for a Hydraulic Actuator,” Proceedings of the IEEE-ICRA 2001, Seoul, Korea (May 21–26, 2001).Google Scholar
24. Goldsmith, P. B., “Global asymptotic stability of hybrid position/force control applied to compliant unilateral constraints,” Mech. Mach. Theory 34 (7), 1009–1021 (1999).CrossRefGoogle Scholar
25. Kwon, D.-S., Woo, K. Y., Song, S. K., Kim, W. S., Cho, H. S., “Microsurgical Telerobot System,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Victoria, Canada (Oct. 13–17, 1998) pp. 945–950.Google Scholar
26. Dafaoui, M., Amirat, Y. and Pontnau, J. F., ‘Analysis and design of a six DOF parallel robot. Modeling, singular configurations and workspace,” IEEE Trans. Robot. Autom. 14 (1), 78–92 (1998).CrossRefGoogle Scholar
27. Chang, P. H., Kim, D. S. and Park, K. C., “Robust force/position control of a robot manipulator using time-delay control,” Control Eng. Pract. 3 (9), 1255–1264 (1995).CrossRefGoogle Scholar
28. Thornton, G. S., “The GEC Tetrabot-a new serial-parallel assembly robot,” Proceedings of the IEEE International Conference on Robotics and Automation, Philadelphia, PA, USA (Apr. 1988) pp. 437–439.Google Scholar
29. Raibert, M. H. and Craig, J. J., “Hybrid position/force control of manipulators,” Trans. ASME 102 (12), 126–133 (1981).Google Scholar
30. Gough, V. E., “Contribution to discussion of papers on research in automobile stability, control and tyre performance,” Proceedings of the Auto Div. Inst. Mech. Eng, (1956–1957) pp. 392–394.Google Scholar