Skip to main content
Log in

Practical Evaluation of Invariant Measures for the Chaotic Response of a Two-Frequency Excited Mechanical Oscillator

  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

This paper presents results which characterize the chaotic response of alow-dimensional mechanical oscillator. An experimental system based on acart rolling on a two-well potential surface has been shown to closelyapproximate a modified form of Duffing's equation. Two-frequency forcingis applied, providing a useful means of varying the dimension of theresponse. Computation of correlation dimension and Lyapunov spectra areperformed on both experimental and numerical data in order to assess theutility of these measures in a practical setting. A specific focus isthe distinction between subharmonic and quasi-periodic forcing, sincethis has a subtle, and interesting, effect on the subsequent dynamics.The results tend to highlight the statistical nature of the measures andthe caution that should be used in their interpretation.

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.

Similar content being viewed by others

References

  1. Virgin, L. N., Introduction to Experimental Nonlinear Dynamics: A Case in Study Mechanical Vibration, Cambridge University Press, Cambridge, 2000.

    Google Scholar 

  2. Wiggins, S., ‘Chaos in the quasiperiodically forced Duffing oscillator’, Physics Letters A 124(3), 1987, 138–142.

    Google Scholar 

  3. Heagy, J. and Ditto, W. L., ‘Dynamics of a two-frequency parametrically driven Duffing oscillator’, Journal of Nonlinear Science 1, 1991, 423–455.

    Google Scholar 

  4. Rao, S. S., Mechanical Vibrations, Addison-Wesley, Reading, MA, 1995.

    Google Scholar 

  5. Takens, F., ‘Detecting strange attractors in turbulence’, in Dynamical Systems and Turbulence, D. A. Rand and L.-S. Young (eds.), Lecture Notes in Mathematics, Vol. 898, Springer-Verlag, New York, 1981, pp. 366–381.

    Google Scholar 

  6. Abarbanel, H. D. I., Brown, R., Sidorowich, J. J., and Tsimring, L. S., ‘The analysis of observed chaotic data in physical systems’, Reviews of Modern Physics 65(4), 1993, 1331–1392.

    Google Scholar 

  7. Fraser, A. M. and Swinney, H. L., ‘Independent coordinates for strange attractors from mutual information’, Physical Review A 33, 1986, 1134–1140.

    Google Scholar 

  8. Sauer, T., Yorke, J. A., and Casdagli, M., ‘Embedology’, Journal of Statistical Physics 65, 1991, 579.

    Google Scholar 

  9. Kantz, H. and Schreiber, T., Nonlinear Time Series Analysis, Cambridge University Press, Cambridge, 1999.

    Google Scholar 

  10. Abarbanel, H. D. I., Analysis of Observed Chaotic Data, Springer-Verlag, New York, 1996.

    Google Scholar 

  11. Brown, R., ‘Using near neighbors to determine embedding dimension for phase space reconstruction’, in Proceedings of the 1st Experimental Chaos Conference, S. Vohra, M. Spano, M. Shlesinger, L. Pecora, and W. Ditto (eds.), World Scientific, Singapore, 1981, pp. 24–30.

    Google Scholar 

  12. Kennel, M. B., Brown, R., and Abarbanel, H. D. I., ‘Determining embedding dimension for phase-space reconstruction using a geometrical construction’, Physical Review A 45(6), 1992, 3403–3411.

    Google Scholar 

  13. Broomhead, D. S. and King, G. P., ‘Extracting qualitative dynamics from experimental data’, Physica D 20, 1986, 217–236.

    Google Scholar 

  14. Banbrook, M., Ushaw, G., and McLaughlin, S., ‘How to extract Lyapunov exponents from short and noisy time series’, IEEE Transactions on Signal Processing 45(5), 1997, 1378–1382.

    Google Scholar 

  15. Kruel, T.-M., Freund, A., and Schneider, F. W., ‘The effect of interactive noise on the driven Brusselator model’, Journal of Chemical Physics 93(1), 1990, 416–427.

    Google Scholar 

  16. Grassberger, P., Schreiber, T., and Schaffrath, C., ‘Nonlinear time sequence analysis’, International Journal of Bifurcation and Chaos 1(3), 1991, 521–547.

    Google Scholar 

  17. Abarbanel, H. D. I. and Kennel, M., ‘Local false nearest neighbors and dynamical dimensions from observed chaotic data’, Physical Review E 47, 1993, 3057–3068.

    Google Scholar 

  18. Williams, G. P., Chaos Theory Tamed, Joseph Henry Press, Washington, DC, 1997.

    Google Scholar 

  19. Grassberger, P. and Proccacia, I., ‘Measuring the strangeness of strange attractors’, Physica D 9, 1983, 189.

    Google Scholar 

  20. Grassberger, P. and Proccacia, I., ‘On the characterization of strange attractors’, Physical Review Letters 50(5), 1983, 346–349.

    Google Scholar 

  21. Albano, A., Mees, A., de Guzman, G., and Rapp, P. E., ‘Data requirements for reliable estimation of correlation dimensions’, in Chaos in Biological Systems, H. Degn, A. V. Holden, and L. F. Isen (eds.), Plenum, New York, 1987, pp. 207–220.

    Google Scholar 

  22. Smith, L. A., ‘Intrinsic limits on dimension calculations’, Physics Letters A 133, 1988, 283.

    Google Scholar 

  23. Nerenberg, M. and C. Essex, C., ‘Correlation dimension and systematic geometric effects’, Physical Review A 42, 1990, 7065–7074.

    Google Scholar 

  24. Ruelle, D., ‘Deterministic chaos: The science and the fiction’, Proceedings of the Royal Society of London A 427, 1990, 241–248.

    Google Scholar 

  25. Theiler, J., ‘Spurious dimension from correlation algorithms applied to limited time-series data’, Physical Review A 34, 1986, 2427.

    Google Scholar 

  26. Grassberger, P., ‘An optimized box-assisted algorithm for fractal dimensions’, Physics Letters A 148, 1990, 63–68.

    Google Scholar 

  27. Jedynak, A., Bach, M., and Timmer, J., ‘Failure of dimension analysis in a simple five dimensional system’, 1770–1780.

  28. Theiler, J., ‘Estimating fractal dimension’, Journal of the Optical Society of America 7(6), 1990, 1055–1073.

    Google Scholar 

  29. Moon, F. C., Chaotic and Fractal Dynamics: An Introduction for Applied Scientists and Engineers, Wiley, New York, 1992.

    Google Scholar 

  30. Wolf, A., Swift, J., Swinney, H., and Vastano, J., ‘Determining Lyapunov exponents from a time series’, Physica D 16, 1984, 285–317.

    Google Scholar 

  31. Peitgen, H.-O., Jürgens, H., and Saupe, D., Chaos and Fractals: New Frontiers of Science, Springer-Verlag, New York, 1992.

    Google Scholar 

  32. Darbyshire, A. G. and Broomhead, D. S., ‘Robust estimation of tangent maps and Liapunov spectra’, Physica D 89, 1996, 287–307.

    Google Scholar 

  33. Eckmann, J.-P., Kamphorst, S., Ruelle, D., and Ciliberto, S., ‘Liapunov exponents from time series’, Physical Review A 34(6), 1986, 4971–4979.

    Google Scholar 

  34. Brown, R., Bryant, P., and Abarbanel, H. D. I., ‘Computing the Lyapunov spectrum of a dynamical system from an observed time series’, Physical Review A 43, 1991, 2787–2806.

    Google Scholar 

  35. Bryant, P., ‘Computation of Lyapunov exponents from experimental data’, in Proceedings of the 1st Experimental Chaos Conference, S. Vohra, M. Spano, M. Shlesinger, L. Pecora, and W. Ditto (eds.), World Scientific, Singapore, 1981, pp. 11–23.

    Google Scholar 

  36. Shin, K. and Hammond, J.-K., ‘The instantaneous Lyapunov exponent and its application to chaotic dynamical systems’, Journal of Sound and Vibration 218, 1998, 389–403.

    Google Scholar 

  37. Gottwald, J. A., Virgin, L. N., and Dowell, E. H., ‘Experimental mimicry of Duffing's equation’, Journal of Sound and Vibration 158, 1992, 447–467.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nichols, J.M., Virgin, L.N. Practical Evaluation of Invariant Measures for the Chaotic Response of a Two-Frequency Excited Mechanical Oscillator. Nonlinear Dynamics 26, 67–86 (2001). https://doi.org/10.1023/A:1012923517945

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1012923517945

Navigation