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A mathematical model for a pneumatically actuated robotic fibre placement system

Published online by Cambridge University Press:  06 September 2002

Gürsel Alici ,
Bijan Shirinzadeh ,
Andrew McConville ,
Chee W. Foong  and
Marcelo Ang
Gürsel Alici*
Affiliation:
Robotics & Mechatronics Research Laboratory, Department of Mechanical Engineering, Monash University, P.O. Box 31, Clayton, Victoria 3800 (Australia)
Bijan Shirinzadeh
Affiliation:
Robotics & Mechatronics Research Laboratory, Department of Mechanical Engineering, Monash University, P.O. Box 31, Clayton, Victoria 3800 (Australia)
Andrew McConville
Affiliation:
Robotics & Mechatronics Research Laboratory, Department of Mechanical Engineering, Monash University, P.O. Box 31, Clayton, Victoria 3800 (Australia)
Chee W. Foong
Affiliation:
Robotics & Mechatronics Research Laboratory, Department of Mechanical Engineering, Monash University, P.O. Box 31, Clayton, Victoria 3800 (Australia)
Marcelo Ang
Affiliation:
National University of Singapore, Department of Mechanical and Production Engineering, 10 Kent Ridge Crescent, 119260 Singapore
*
Email: gursel.alici@eng.monash.edu.au
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Summary

In this paper, a lumped parameter model of a robotic fibre placement system consisting of a Motoman SK-120 robot, a force/torque sensor, a pneumatic actuator and a stiff workpiece holder is developed and experimentally verified for the purpose of predicting and characterising the dynamic behaviour of the fibre placement system. Special attention has been given to the dynamics of the actuator which is represented as a mass confined to move between two non-linear springs and dampers. The overall model containing manipulator, force sensor, pneumatic actuator and the workpiece holder dynamics is of the tenth order. Step response experiments were conducted to verify the model and to determine the approximate values of the parameters in the mathematical model. The results prove that the established model is accurate enough to explain the dynamic behaviour of the fibre placement system and it can be employed to quantify the influence of the dynamics of the pneumatic actuator on the constant force-based fibre placement. The well-known fact that the dynamics of the pneumatic actuator varies with the piston position has also been experimentally demonstrated.

Keywords

Pneumatic actuatorsMathematical modellingRobotic fibre placementForce sensing
Type
Research Article
Information
Robotica , Volume 20 , Issue 5 , September 2002 , pp. 545 - 551
Copyright
Copyright © Cambridge University Press 2002

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References

1. Paul, A. K., Mishra, J. K. and Radke, M. G., “Reduced order sliding mode control for pneumatic actuator”, IEEE Transactions on Control Systems Technology 2(3), 271–276 (September, 1994).CrossRefGoogle Scholar
2. Bobrow, J. E. and McDonell, B. W., “Modeling, identification, and control of a pneumatically actuated, force controllable robot”, IEEE Transactions on Robotics and Automation 14(5), 732–742 (October, 1998).Google Scholar
3. Liu, S. and Bobrow, J. E., “An analysis of a pneumatic servo system and its application to a computer-controlled robot”, ASME Journal of Dynamic Systems, Measurement, and Control 110, 228–235 (September, 1988).Google Scholar
4. Pfreundschuh, G. H., Kumar, V. and Sugar, T. G., “Design and control of a 3 DOF in-parallel actuated manipulator”, Proceedings of the 1991 IEEE International Conference on Robotics and Automation, Sacramento, California (April, 1991) pp. 1659–1664.Google Scholar
5. Van Varseveld, R. B. and Bone, G. M., “Accurate position control of a pneumatic actuator using on/off solenoid valves”, IEEE/ASME Transactions on Mechatronics 2(3), 195–204 (September, 1997).Google Scholar
6. Andersen, B. W., The Analysis and Design of Pneumatic Systems (John Wiley and Sons, 1967).Google Scholar
7. Pu, J. and Weston, R. H., “A new generation of pneumatic servos for industrial robots”, Robotica 7, Part 1, 17–23 (1989).Google Scholar
8. Merchant, J. A., Street, M. J., Gurney, P. and Benson, J. A., “Design and testing of a servo controller for pneumatic cylinders”, Proc. Inst. Mech. Eng. E 203, 21–27 (1989).Google Scholar
9. Linnett, J. A. and Smith, M. C. “An accurate low-friction pneumatic position control system”, Proc. Inst. Mech. Eng. B 203, 159–165 (1989).Google Scholar
10. Kawamura, S., Miyata, K., Hanafusa, H. and Isida, K., “PI type hierarchical feedback control scheme for pneumatic robots”, Proceedings of the 1989 IEEE International Conference on Robotics and Automation (1989) pp. 1853–1858.Google Scholar
11. Mannetje, J. J., “Pneumatic servo design method improves system bandwidth twenty-fold”, Control Engineering 79–83 (June, 1981).Google Scholar
12. Pu, J., Weston, R. H. and Moore, P. R., “Digital motion control and profile planning for pneumatic servos”, ASME Journal of Dynamic Systems, Measurement, and Control 114, 634–640 (December, 1992).Google Scholar
13. Bobrow, J. E. and Jabbari, F., “Adaptive pneumatic force actuation and position control”, ASME Journal of Dynamic Systems, Measurement, and Control 113, 267–272 (June, 1991).Google Scholar
14. Guvenc, L. and Srinivasan, K., “Modeling and parameter identification of a pneumatic constant force device”, Journal of Engineering and Environmental Sciences 24, 383–399 (2000).Google Scholar
15. Alici, G. and Daniel, R. W., “Static Friction Effects during Hard-on-Hard Contact Tasks and Their Implications for Manipulator Design.” Int. J. Robotics Research 13(6), 508–520 (December, 1994).Google Scholar
16. Alici, G. and Daniel, R. W., “Development and Verification of a Mathematical Model for Robot Force Control via Measuring an Input/Output Relationship and Force Control Experiments.” Int. J. Modelling and Simulation 17(2), 107–119 (1997).Google Scholar