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Adaptive control of flexible joint robots derived from arm energy considerations

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Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 151))

Abstract

Almost all industrial robots exhibit joint flexibility due to mechanical compliance of their gear boxes. In this paper we outline the design of three controllers for flexible joint robots. Two of the three controllers are suitable for parameter adaptation, the candidate Lyapunov functions for these two controllers are derived from arm energy considerations.

The desired actuator trajectory in a flexible joint robot is dependent not only on the desired kinematic trajectory of the link but also on the link dynamics. Unfortunately, link dynamic parameters are unknown in most cases, as a result the desired actuator trajectory is also unknown. To overcome this difficulty, a number of control schemes require the use of link acceleration and link jerk feedback. In this paper we describe three control schemes for flexible joint robots which do not use link jerk or acceleration. One of the controllers is suitable for trajectory tracking when the robot parameters are known in advance. The other two control laws are derived from candidate Lyapunov functions which resemble the energy of the arm deviating from the desired trajectory. Trajectory tracking and adaptation of robot arm parameters are possible with two of the controllers described in this paper. Our control schemes do not require the numerical differentiation of the velocity signal, or the inversion of the inertial matrices. Simulations are presented to verify the validity of the control scheme. The superiority of the proposed scheme over existing rigid robot adaptive schemes is also illustrated through simulation.

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J. M. Skowronski H. Flashner R. S. Guttalu

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© 1991 Springer-Verlag

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Ahmad, S., Mrad, F. (1991). Adaptive control of flexible joint robots derived from arm energy considerations. In: Skowronski, J.M., Flashner, H., Guttalu, R.S. (eds) Mechanics and Control. Lecture Notes in Control and Information Sciences, vol 151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0006713

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  • DOI: https://doi.org/10.1007/BFb0006713

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53517-1

  • Online ISBN: 978-3-540-46752-6

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