Skip to main content
Log in

Better Stability with Measurement Errors

  • Published:
Journal of Statistical Physics Aims and scope Submit manuscript

Abstract

Often it is desirable to stabilize a system around an optimal state. This can be effectively accomplished using feedback control, where the system deviation from the desired state is measured in order to determine the magnitude of the restoring force to be applied. Contrary to conventional wisdom, i.e. that a more precise measurement is expected to improve the system stability, here we demonstrate that a certain degree of measurement error can improve the system stability. We exemplify the implications of this finding with numerical examples drawn from various fields, such as the operation of a temperature controller, the confinement of a microscopic particle, the localization of a target by a microswimmer, and the control of a population.

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

Similar content being viewed by others

References

  1. B. C. Kuo and F. Golnaraghi, Automatic control systems (John Wiley & Sons, Inc., New York, NY, 2008), 8th ed

  2. H. C. Berg, E. coli in Motion (Springer Verlag, Heidelberg, Germany, 2004)

  3. Botsford, L.W., Castilla, J.C., Peterson, C.H.: The management of fisheries and marine ecosystems. Science 277, 509 (1997)

    Article  Google Scholar 

  4. Meffe, G., Nielsen, L., Knight, R.L., Schenborn, D.: Ecosystem management: Adaptive, community-based conservation. Island Press, Washington, DC (2012)

    Google Scholar 

  5. Franklin, G.F., Powell, J.D., Emami-Naeini, A.: Feedback control of dynamic systems, vol. 320. Addison-Wesley, Reading, MA (1991)

    MATH  Google Scholar 

  6. Øksendal, B.: Stochastic differential equations. Springer Verlag, Heidelberg, Germany (2003)

    Book  MATH  Google Scholar 

  7. Vilar, J.M.G.: Rubí, Noise suppression by noise, J.M. Phys. Rev. Lett. 86, 950–953 (2001)

    Article  ADS  Google Scholar 

  8. Volpe, G., Wehr, J., Petrov, D., Rubi, J.M.: Thermal noise suppression: How much does it cost? J. Phys. A: Math. Theo. 42, 095005 (2009)

    Article  ADS  MathSciNet  MATH  Google Scholar 

  9. Kloeden, P.E., Platen, E.: Numerical solution of stochastic differential equations. Springer Verlag, Heidelberg, Germany (1999)

    MATH  Google Scholar 

  10. Volpe, G., Volpe, G.: Simulation of a brownian particle in an optical trap Am. J. Phys. 81, 224–231 (2013)

    ADS  Google Scholar 

  11. Ohta, A.T., Chiou, P.-Y., Phan, H.L., Sherwood, S.W., Yang, J.M., Lau, A.N.K., Hsu, H.-Y., Jamshidi, A., Wu, M.C.: IEEE, : Optically controlled cell discrimination and trapping using optoelectronic tweezers. J. Sel. Top. Quant. El. 13, 235–243 (2007)

    Article  Google Scholar 

  12. Crocker, J.C., Grier, D.G.: Methods of digital video microscopy for colloidal studies. J. Colloid Interfac. Sci. 179, 298–310 (1996)

    Article  Google Scholar 

  13. Rohrbach, A., Stelzer, E.H.K.: Three-dimensional position detection of optically trapped dielectric particles. J. Appl. Phys. 91, 5474–5488 (2002)

    Article  ADS  Google Scholar 

  14. Ebbens, S.J., Howse, J.R.: In pursuit of propulsion at the nanoscale. Soft Matter 6, 726–738 (2010)

    Article  ADS  Google Scholar 

  15. C. Bechinger, R. Di Leonardo, H. Löwen, C. Reichhardt, G. Volpe, and G. Volpe, Active Brownian particles in complex and crowded environments, arXiv:1602.00081 (2016)

  16. Berg, H.C., Brown, D.A.: Chemotaxis in escherichia coli analysed by three-dimensional tracking. Nature 239, 500–504 (1972)

    Article  ADS  Google Scholar 

  17. Mijalkov, M., McDaniel, A., Wehr, J., Volpe, G.: Engineering sensorial delay to control phototaxis and emergent collective behaviors. Phys. Rev. X 6, 011008 (2016)

    Google Scholar 

  18. Volpe, G., Gigan, S., Volpe, G.: Simulation of the active Brownian motion of a microswimmer. Am. J. Phys. 82, 659–664 (2014)

    Article  ADS  Google Scholar 

Download references

Acknowledgments

GV has been partially financially supported by Marie Curie Career Integration Grant (MC-CIG) under Grant PCIG11 GA-2012-321726 and a Distinguished Young Scientist award of the Turkish Academy of Sciences (TÜBA).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Giovanni Volpe.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (mp4 6498 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Argun, A., Volpe, G. Better Stability with Measurement Errors. J Stat Phys 163, 1477–1485 (2016). https://doi.org/10.1007/s10955-016-1518-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10955-016-1518-8

Keywords

Navigation