Skip to main content
Log in

Parameter identification for multibody systems expressed in differential-algebraic form

  • Published:
Multibody System Dynamics Aims and scope Submit manuscript

Abstract

The ability of a multibody dynamic model to accurately predict the response of a physical system relies heavily on the use of appropriate system parameters in the mathematical model. Thus, the identification of unknown system parameters (or parameters that are known only approximately) is of fundamental importance. If experimental measurements are available for a mechanical system, the parameters in the corresponding mathematical model can be identified by minimizing the error between the model response and the experimental data. Existing work on parameter estimation using linear regression requires the elimination of the Lagrange multipliers from the dynamic equations to obtain a system of ordinary differential equations in the independent coordinates. The elimination of the Lagrange multipliers may be a nontrivial task, however, as it requires the assembly of an orthogonal complement of the Jacobian. In this work, we present an approach to identify inertial system parameters and Lagrange multipliers simultaneously by exploiting the structure of the index-3 differential-algebraic equations of motion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. MapleSim is a trademark of Waterloo Maple, Inc.

  2. Matlab is a registered trademark of The MathWorks, Inc.

References

  1. Chenut, X., Fisette, P., Samin, J.C.: Recursive formalism with a minimal dynamic parameterization for the identification and simulation of multibody systems. Application to the human body. Multibody Syst. Dyn. 8(2), 117–140 (2002)

    Article  MATH  Google Scholar 

  2. Ebrahimi, S., Kövecses, J.: Sensitivity analysis for estimation of inertial parameters of multibody mechanical systems. Mech. Syst. Signal Process. 24(1), 19–28 (2010)

    Article  Google Scholar 

  3. Ebrahimi, S., Kövecses, J.: Unit homogenization for estimation of inertial parameters of multibody mechanical systems. Mech. Mach. Theory 45(3), 438–453 (2010)

    Article  MATH  Google Scholar 

  4. Fisette, P., Raucent, B., Samin, J.C.: Minimal dynamic characterization of tree-like multibody systems. Nonlinear Dyn. 9(1–2), 165–184 (1996)

    Article  MathSciNet  Google Scholar 

  5. Gautier, M., Khalil, W.: Direct calculation of minimum set of inertial parameters of serial robots. IEEE Trans. Robot. Autom. 6(3), 368–373 (1990)

    Article  Google Scholar 

  6. Grupp, F., Kortüm, W.: Parameter identification of nonlinear descriptor systems. In: Schiehlen, W. (ed.) Advanced Multibody System Dynamics: Simulation and Software Tools, Solid Mechanics and Its Applications, vol. 20, pp. 457–462. Kluwer Academic, Dordrecht (1993)

    Chapter  Google Scholar 

  7. Haug, E.J.: Computer Aided Kinematics and Dynamics of Mechanical Systems—Volume I: Basic Methods. Allyn and Bacon, Boston (1989)

    Google Scholar 

  8. Kövecses, J., Ebrahimi, S.: Parameter analysis and normalization for the dynamics and design of multibody systems. J. Comput. Nonlinear Dyn. 4(3), 031008 (2009)

    Article  Google Scholar 

  9. Mariti, L., Belfiore, N.P., Pennestrì, E., Valentini, P.P.: Comparison of solution strategies for multibody dynamics equations. Int. J. Numer. Methods Eng. 88(7), 637–656 (2011)

    Article  MATH  Google Scholar 

  10. Montgomery, D.C., Peck, E.A., Vining, G.G.: Introduction to Linear Regression Analysis, 3rd edn. Wiley, New York (2001)

    MATH  Google Scholar 

  11. Mooney, C.Z.: Monte Carlo Simulation, Quantitative Applications in the Social Sciences, vol. 116. Sage Publications, Thousand Oaks (1997)

    Google Scholar 

  12. Raucent, B., Campion, G., Bastin, G., Samin, J.C., Willems, P.Y.: Identification of the barycentric parameters of robot manipulators from external measurements. Automatica 28(5), 1011–1016 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  13. Schmidt, T., Müller, P.C.: A parameter estimation method for multibody systems with constraints. In: Schiehlen, W. (ed.) Advanced Multibody System Dynamics: Simulation and Software Tools, Solid Mechanics and Its Applications, vol. 20, pp. 427–432. Kluwer Academic, Dordrecht (1993)

    Chapter  Google Scholar 

  14. Shome, S.S., Beale, D.G., Wang, D.: A general method for estimating dynamic parameters of spatial mechanisms. Nonlinear Dyn. 16(4), 349–368 (1998)

    Article  MATH  Google Scholar 

  15. The MathWorks, Inc.: Matlab R2007a Help: mldivide (2007)

  16. Vyasarayani, C.P., Uchida, T., McPhee, J.: Nonlinear parameter identification in multibody systems using homotopy continuation. J. Comput. Nonlinear Dyn. 7(1), 011012 (2012)

    Article  Google Scholar 

  17. Weisberg, S.: Applied Linear Regression. Wiley Series in Probability and Statistics, vol. 528, 3rd edn. Wiley, Hoboken (2005)

    Book  MATH  Google Scholar 

Download references

Acknowledgements

T.U. and J.M. gratefully acknowledge the financial support provided by the Natural Sciences and Engineering Research Council of Canada (NSERC), and the NSERC/Toyota/Maplesoft Industrial Research Chair program. C.P.V. and M.S. acknowledge the financial support received from the Ontario Centres of Excellence.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Uchida.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Uchida, T., Vyasarayani, C.P., Smart, M. et al. Parameter identification for multibody systems expressed in differential-algebraic form. Multibody Syst Dyn 31, 393–403 (2014). https://doi.org/10.1007/s11044-013-9390-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11044-013-9390-7

Keywords

Navigation