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Modelling and Identification of Robots with Joint and Drive Flexibilities

  • Toon Hardeman
  • Ronald Aarts
  • Ben Jonker
Part of the Solid Mechanics and its Applications book series (SMIA, volume 130)

Abstract

This paper deals with modelling and identification of flexible-joint robot models that can be used for dynamic simulation and model based control of industrial robots. A nonlinear finite element based method is used to derive the dynamic equations of motion in a form suitable for both simulation and identification. The latter requires that the equations of motion are linear in the dynamic parameters. For accurate simulations of the robot tip motion the model should describe the relevant dynamic properties such as joint friction and flexibilities. Both the drive and the joint flexibilities are included in the model. Joint friction is described by means of a static friction model, including Coulomb and viscous friction components. The dynamic parameters describing mass, inertia, stiffness, damping and friction properties are obtained from a least squares solution of an over determined linear system assembled from closed loop identification experiments. In the identification experiment the robot moves along a prescribed trajectory while all joint angles, flexible deformations and driving torques are recorded. In order to excite joint vibrations during the identification feed forward torques at frequencies above the bandwidth of the control system are superposed on the joint torques. The applicability of the method is demonstrated in a numerical study of a four link industrial robot.

Keywords

parameter identification flexible/elastic-joint robots nonlinear finite element method 

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References

  1. Albu-Schäffer, A. and Hirzinger, G. (2001). Parameter identification and passivity based joint control for a 7dof torque controlled light weight robot. In IEEE International Conference on Robotics and Automation, pp. 2852–2858.Google Scholar
  2. Geradin, M., Robert, G. and Buchet, P. (1986). Finite Element Methods for Nonlinear Problems, chapter “Kinematic and Dynamic Analysis of Mechanisms a Fininite Element Approach Based on Euler Parameters”. Springer-Verlag, Berlin.Google Scholar
  3. Hardeman, T., Aarts, R.G.K.M. and Jonker, J.B. (2005). A finite element formulation for dynamic parameter identification of robot manipulators. Submitted to Multibody System Dynamics.Google Scholar
  4. Huang, J.T. (2003). A new approach to parametric identification of a single-link flexible joint manipulator. Jounal of Intelligent and Robotic Systems, 37:273–284.zbMATHGoogle Scholar
  5. Jonker, J.B. (1990). A finite element dynamic analysis of flexible manipulators. International Journal of Robotic Research, 9:59–74.Google Scholar
  6. Khan, I.R. and Ohba, R. (2003). Taylor series based finite differentce approximations of higher degree derivatives. Journal of Computational and Applied Mathematics, 154:115–124.CrossRefMathSciNetGoogle Scholar
  7. Lawson, C.L. and Hanson, R.J. (1974). Solving Least Squares Problems. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  8. Östring, M, Gunnarsson, S. and Norrlöf, M. (2003). Closed-loop identification of an industrial robot containing flexibilities. Control Engineering Practice, 11:291–300.CrossRefGoogle Scholar
  9. Pham, M.T., Gautier, M. and Poignet, Ph. (2001). Identification of joint stiffness with bandpass filtering. In IEEE International Conference on Robotics and Automation, pp. 2867–2872.Google Scholar
  10. Pham, M.T., Gautier, M. and Poignet, Ph. (2002). Accelerometer based identification of mechanical systems. In IEEE International Conference on Robotics and Automation, pp. 4293–4298.Google Scholar
  11. Schwab, A.L. and Meijaard, J.P. (1999). The belt, gear, bearing and hinge as special finite elements for kinematic and dynamic analysis of mechanisms and machines. In Dynamics, Nonlinear Oscillations, Rotor Dynamics and Software Development.Google Scholar
  12. Spong, M.W. (1987). Modeling and control of elastic joint robots. Journal of Dynamic Systems, Measurement, and Control, 109:310–319.zbMATHGoogle Scholar
  13. Tsaprounis, C.J. and Aspragathos, N.A. (2000). Adaptive tracking controller for rigid-link elastic-joint robots with link acceleration astimation. Journal of Intelligent and Robotic Systems, 27:68–83.CrossRefGoogle Scholar
  14. Yoshikawa, T., Ohta, A. and Kanaoko, K. (2001). State estimation and parameter identification of flexible manipulators based on visual sensor and virtual joint method. In IEEE International Conference on Robotics and Automation, pp. 2840–2845.Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • Toon Hardeman
    • 1
  • Ronald Aarts
    • 1
  • Ben Jonker
    • 1
  1. 1.Faculty of Engineering TechnologyUniversity of TwenteThe Netherlands

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