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Adaptive Control of Nonlinear Dynamic SCARA Type of Manipulators*

Published online by Cambridge University Press:  09 March 2009

Devendra P. Garg
Devendra P. Garg
Affiliation:
Department of Mechanical Engineering, Duke University, Durham, NC 27706 (USA)
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Summary

This paper deals with an investigation of the relative importance of robotic characteristics typically associated with nonlinear manipulators. An IBM 7540 SCARA type of robot is used for simulation, and results are presented for decentralized proportional plus derivative control action applied to individual robot joints, and the use of an adaptive computed torque control strategy is illustrated. The influence of variations in payload and robot parameters on trajectory tracking is also shown.

Keywords

Adaptive controlSCARA robotNonlinearRobot parameters.
Type
Article
Information
Robotica , Volume 9 , Issue 3 , July 1991 , pp. 319 - 326
Copyright
Copyright © Cambridge University Press 1991

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References

1.Garg, D.P., “Nonlinear Dynamic Characteristics in Mechanical Manipulators” Proceedings of the 20th Modeling and Simulation Conference 20, Part 5, 2125–2129 (University of Pittsburgh,Pittsburgh, PA, 05 4–5, 1989).Google Scholar
2.Vossoughi, R. and Donath, M., “Robot Hand Impedence Control in the Presence of Mechanical Nonlinearities”, ASME Special Publication No. PED-15, 67–77 (ASME, New York, NY, 11, 1985).Google Scholar
3.Garg, D., Shanidze, Z. and Rondeli, E., “Global Stability of Solutions of Nonlinear Control Systems” Int. J. Systems Science 20, No. 10, 1909–1924 (10, 1989).Google Scholar
4.Singh, S.N., “Control and Stabilization of Nonlinear Uncertain Elastic Robot Arm” IEEE Transactions on Aerospace and Electronic Systems 24, No. 2, 148–155 (03 1988).CrossRefGoogle Scholar
5.Horowitz, R. and Tomizuka, M., “Adaptive Control Scheme for Mechanical Manipulators—Compensation of Nonlinearity and Decoupling Control” J. Dynamic Systems, Measurement, and Control, Transactions of the ASME, Series G, 108, No. 2, 127–135 (06, 1986).Google Scholar
6.Menon, R. and Garg, D., “Exact Linearization of Nonlinear Manipulator Models Using Adaptive Control” Proceedings of the American Control Conference, 2, 924–929, (Atlanta GA, 06 15–17, 1988).Google Scholar
7.Walker, M.W., “Adaptive Control of Manipulators Containing Closed Kinematic Loops” IEEE Transactions on Robotics and Automation 6, No. 1, 10–19 (02 1990).Google Scholar
8.Garg, D., “Multi-arm Coordination and Control”. In: Dynamics and Control of Multibody/Robotic Systems with Space Applications, ASME Special Publication DSC-15 (12 1989) pp. 27–35.Google Scholar
9.Slotine, J.J. and Li, W., “Adaptive Manipulator Control: A Case Study” Proceedings of the IEEE International Conference on Robotics and Automation 3, 1392–1400 (03, 1987).Google Scholar
10.Sadegh, N. and Horowitz, R., “Stability Analysis of an Adaptive Controller for Robotic Manipulators” Proceedings of the IEEE Conference on Robotics and Automation1223–1239 (03, 1987).Google Scholar
11.Choi, Y.K. and Bien, Z., “Decentralized Adaptive Control Scheme for Control of a Multi-Arm-Type Robot” Int. J. Control 48, No. 4, 1715–1722 (10, 1988).CrossRefGoogle Scholar
12.Yuh, J., “The Effect of Unmodeled Flexible Dynamics in Discrete-Time Model Reference Adaptive Control of a Flexible Single-Link Robot” Proceedings of the 26th IEEE Conference on Decision and Control 2, 1037–1038 (12, 1987).Google Scholar
13.Naganathan, G. and Soni, A., “Nonlinear Modeling of Kinematic and Flexibility Effects in Manipulator Design” ASME Paper No. 86-DET-88 (10, 1986).Google Scholar
14.Leahy, M. and Saridis, G., “Compensation of unmodeled PUMA Manipulator Dynamics” Proceedings of the IEEE International Conference on Robotics and Automation 1, 151–156 (03, 1987).Google Scholar
15.Hsia, T.C., Lasky, T.A. and Guo, Z.Y., “Robust Independent Robot Joint Control: Design and Experimentation” Proceedings of 1988 IEEE International Conference on Robotics and Automation 3, 1329–1334 (Philadelphia, 1988).Google Scholar
16.Garg, D. and Ellingboe, B., “Controllers for Automated Assembly Operation”. In: Dynamic Systems: Modeling and Control, ASME Publication No. DSC-1 (1985) pp. 225–234.Google Scholar
17.Stokić, D. and Vukobratović, M., “Robustness of Decentralized Robot Controller to Payload Variation” J. Robotic Systems 5, No. 5, 471–495 (1988).CrossRefGoogle Scholar
18.Bejczy, A. and Tarn, T., “Robot Control as a System Control Problem”. In: Theory of Robots (Kopacek, P. et al. , eds.) (Pergamon Press, Oxford, UK, 1988) pp. 1–13.Google Scholar
19.Garg, D. and Ellingboe, B., “P and PI Control in Robotic Insertion Assembly Processes” Proceedings of the 17th Annual Pittsburgh Conference on Modeling and Simulation,University of Pittsburgh, PA 15, Pt. 5, 1721–1725 (04, 1986).Google Scholar
20.Jayasuriya, S. and Kee, C., “Controller Design Guaranteeing Precise Trajectory Following for a Robotic Manipulator” Proceedings of the American Control Conference66–71 (06, 1987).Google Scholar
21.Berlin, F., Grimm, W. and Frank, P., “On Robot Motion Control with Acceleration Feedback”. In: Selected Papers from the 2nd IFAC Symposium, Karlsruhe, FRG, (U. Rembold, ed.) (10 5–7, 1988) pp. 183–188.CrossRefGoogle Scholar
22.Garg, D. and Menon, R., “Damping in Light Weight Robotic Manipulators” Proceedings of the 17th Annual Pittsburgh Conference on Modeling and Simulation 15, Pt. 5, 1733–1737 (04, 1986).Google Scholar
23.Garg, D. and Shankar, S., “End Point Deflection Studies of the GE P-50 Robot” Proceedings of the 17th Annual Pittsburgh Conference on Modeling and Simulation 15, Pt. 5, 1727–1731 (04, 1986).Google Scholar
24.Shahinpoor, M., “Dynamics”. In: International Encyclope dia of Robotics 1 (Dorf, R.C., ed.) Wiley, New York, (1988) pp. 329–347.Google Scholar
25.Garg, D., “Path Planning and Collision Avoidance for a Five Degree of Freedom Robot”. In: Intelligent Control, ASME Special Publication Number DSC-5, 19–25 (12, 1987).Google Scholar
26.Paul, R., Robot Manipulators: Mathematics, Programming, and Control (MIT Press, Cambridge, MA, 1981).Google Scholar
27.Khosla, P. and Kanade, T., “An Algorithm to Estimate Manipulator Dynamics Parameters” Technical Report No. CMU-RI-TR-87–7 (03, 1987).Google Scholar
28.Ha, I., Ko, S. and Kwon, S., “An efficient Algorithm for the Model Parameters of Robotic Manipulators” IEEE Transactions on Robotics and Automation 5, No. 3, 386–394 (06, 1989).CrossRefGoogle Scholar
29.Craig, J., Ping, H. and Sastry, S., “Adaptive Control of Mechanical Manipulators” Int. J. Robotics Research 6, No. 2, 16–17 (Summer, 1987).Google Scholar
30.Landau, Y., Adaptive Control: Model Reference Approach (Marcel Dekker, New York, 1979).Google Scholar
31.Schwartz, H. and Warshaw, G., “On the Richness Condition for Robot Adaptive Control” Robotics Research 43–49, (1989).Google Scholar
32.Seraji, H., “Decentralized Adaptive Control of Manipulators: Theory, Simulation and Experimentation” IEEE Transactions on Robotics and Automation 5, No. 2, 183–209 (04, 1989).CrossRefGoogle Scholar
33.Ozguner, U. et al. , “Decentralized Variable Structure Control of a Two-Arm Robotic System” Proceedings of the IEEE International Conference on Robotics and Automation 3, 1248–1254 (03, 1987).Google Scholar
34.Skowronski, J., “Adaptive Nonlinear Model Following and Avoidance Under Uncertainty” IEEE Transactions on Circuits and Systems 35, No. 9, 1082–1088 (09, 1988).CrossRefGoogle Scholar
35.Yuan, B., and Book, W., “Decentralized Adaptive Control of Robot Manipulators with Robust Stabilization Design” Proceedings of the American Control Conference 1, 102–107 (1988).Google Scholar
36.Duarte, M. and Narendra, K., “A New Approach to Model Reference Adaptive Control”, Int. J. Adaptive Control and Signal Processing 3, 53–73 (1989).Google Scholar
37.Sastry, S. and Bodson, M., Adaptive Control: Stability, Convergence, and Robustness (Prentice-Hall, New York, 1989).Google Scholar
38.Narendra, K. and Boskovic, J., “A Combined Direct, Indirect and Variable Structure Method for Robust Adaptive Control” Proceedings of the American Control Conference 1, 543–548 (1990).Google Scholar