Skip to main content
Log in

Passive identification of heat equation coefficients with account for errors in estimating the state of the object and measuring system

  • Analysis and Synthesis of Signals and Images
  • Published:
Optoelectronics, Instrumentation and Data Processing Aims and scope

Abstract

This paper describes the problem of passive identification of heat equation coefficients with account for the noise of the behavior of the object dynamics model and for the noise of the measuring system model. The use of the finite difference method allowed for reducing the solution of partial differential equations to the solution of a system of linear finite-difference and algebraic equations described by models in the form of a state space. Presentation of the heat equation in form of such a model makes it possible to apply the Kalman filter algorithm for the reliable estimation of the behavior of the object under study.

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. I. G. Aramanovich and V. I. Levin, Equations of Mathematical Physics (Nauka, Moscow, 1969) [in Russian].

    Google Scholar 

  2. I. N. Sinitsyn, Kalman and Pugachev Filters: Study Guide (Universitetskaya Kniga, Logos, Moscow, 2006) [in Russian].

    Google Scholar 

  3. G. A. Abdenova, “Structural and Parametric Identification of Systems with Distributed Parameters Using the “Input — State — Output” Models,” Nauch. Vestn. Nov. Gos. Tekh. Univ. 1 (38), 9–16 (2006).

    Google Scholar 

  4. V. G. Gorsky and Yu. P. Adler, and A. M. Talalai, Scheduling Industrial Experiments. Dynamics Models (Metallurgiya, Moscow, 1978) [in Russian].

    Google Scholar 

  5. R. Mehra, “Identification and Adaptive Kalman Filtering,” Mechanics 3, 34–52 (1971).

    Google Scholar 

  6. G. A. Abdenova, “Forecasting Time Series Level Values on the Basis of the Kalman Filter Equations,” Polzunovskii Vestnik 2, 4–6 (2010).

    Google Scholar 

  7. N. K. Smolentsev, Fundamentals of the Wavelet Theory. Wavelets in MATLAB (DMK Press, Moscow, 2005) [in Russian].

    Google Scholar 

  8. A. Zh. Abdenov, “Increasing the Information Content of Measurements for Stochastic Dynamical Systems Based on the Optimization of the Spectral Density of Input Signal,” Avtometriya 35 (1), 77–93 (1999).

    Google Scholar 

  9. A. Zh. Abdenov, “Scheduling the Autocorrelation Function of Input Signal for Stochastic Continuous Discrete Dynamical Systems,” Avtometriya 41 (2), 81–97 (2005).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Zh. Abdenov.

Additional information

Original Russian Text © A.Zh. Abdenov, G. A. Abdenova, 2016, published in Avtometriya, 2016, Vol. 52, No. 2, pp. 43–51.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abdenov, A.Z., Abdenova, G.A. Passive identification of heat equation coefficients with account for errors in estimating the state of the object and measuring system. Optoelectron.Instrument.Proc. 52, 141–147 (2016). https://doi.org/10.3103/S8756699016020059

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S8756699016020059

Keywords

Navigation