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Forces of reaction and neighbouring Hamilton's principle in the tracking control of manipulators via a sliding scheme

Published online by Cambridge University Press:  09 March 2009

Guy Jumarie
Affiliation:
Department of Mathematics and Computer ScienceUniversité du Québec à MontréalP.O. Box 8888StA, Montreal, QUE, H3C 3P8 (Canada)

Summary

It is shown that if one comes back to the formulation of the Hamilton's variational principle, it is then possible to obtain new viewpoints on the tracking control of robot manipulators. First, the Lagrange multiplier associated to the sliding surface can be interpretated in terms of control effort and/or forces of reaction of the mechanical system. Secondly, one can use the Taylor expansion of the mechanical Lagrangian, combined with a neighbour- ing Hamilton's principle, to obtain control schemes via sliding surfaces. Thirdly, a perturbation approach combined with the neighbouring Hamilton's principle provides results on the robustness of the control.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1993

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References

1.Craig, J. J.Introduction to Robotics: Mechanics and Control (Addison Wesley, Wokingham, 1986).Google Scholar
2.Dubowsky, S. and Desforges, D.T.The application of model-reference adaptive control to robotic manipulatorASMEJ. Dyn. Syst. Meas. Control 101, 193200s (1979).CrossRefGoogle Scholar
3.Horowitz, R. and Tomizuka, M.An adaptive control scheme for mechanical manipulator-compensation of nonlinearities and decoupling controlASMEJ. Dyn. Syst. Meas. Control 108, 127135 (1986).CrossRefGoogle Scholar
4.Koivo, A. and Guo, T.Adaptive linear controller for robotic manipulatorsIEEE Trans. Automatic Control 28, 162171 (1983).CrossRefGoogle Scholar
5.Lee, C.S.G. and Chung, M. J.An adaptive control strategy for mechanical manipulatorsIEEE Trans. Automatic Control 29, 837840 (1984).CrossRefGoogle Scholar
6.Slotine, J. J. and Li, W.Adaptive manipulator control: a case studyIEEE Trans. Automatic Control 33, 9951003 (1988).CrossRefGoogle Scholar
7.Craig, J. J., Hsu, P. and Sastry, S. S.Adaptive control of mechanical manipulatorsInt. J. Robotics Research 6, 1628 (1987).CrossRefGoogle Scholar
8.Young, K.Controller design for a manipulator using theory of variable structure systemsIEEE Trans. Systems, Man and Cybernetics 8, 101109 (1978).CrossRefGoogle Scholar
9.Utkin, V.Variable, structure systems with sliding modesIEEE Trans. Automatic Control 22, 211222 (1977).CrossRefGoogle Scholar
10.S-K, Tso, Y., Xu and H-Y, ShumVariable structure model reference adaptive control of robot manipulators J. Systems Engineering 1, No. 1, 2230 (1991).Google Scholar
11.G., JumarieA new approach to control and filtering of mechanical systems by using the estimates of their LagrangiansJ. Optimization Theory and Applications 68, No. 2, 289304 (1991).Google Scholar
12.Asada, H. and Slotine, J. J.Robot Analysis and Control (John Wiley, New York, 1986).Google Scholar
13.Stengeld, R. F.Stochastic Optimal Control (John Wiley, New York, 1986).Google Scholar
14.Bryson, A. E. and Ho, Y. C.Applied Optimal Control (John Wiley, 1975).Google Scholar