Russian Physics Journal

, Volume 58, Issue 7, pp 1010–1017 | Cite as

State Estimation for Nonstationary Discrete Systems with Unknown Input Using Compensations

MATHEMATICAL PROCESSING OF PHYSICS EXPERIMENTAL DATA
First Online:
Received:

The problem of constructing state estimations for linear non-stationary dynamic systems with discrete time is considered for a model with unknown input. A non-stationary filtering algorithm with compensation for the constant component and estimation of the unknown changing input component by the least squares method is suggested. Results of statistical simulation are presented. The algorithm can be used for solving problems of processing information obtained as a result of observations over physical processes.

Keywords

state estimations discrete non-stationary system unknown input compensation least squares method 
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    R. E. Kalman and R. Busy, Trans. ASME, J. Basic Eng., 83, 95–108 (1961).CrossRefGoogle Scholar
  2. 2.
    B. Friedland, IEEE Trans. Automat. Contr., AC-14, 359–367 (1969).MathSciNetCrossRefGoogle Scholar
  3. 3.
    J. Chen and R. J. Patton, IEE Proc. Control Theory Appl., 143, 31–36 (1996).MATHCrossRefGoogle Scholar
  4. 4.
    M. Darouach, M. Zasadzinski, and S. J. Xu, IEEE Trans. Automat. Contr., AC-39, 606 (1999).MathSciNetGoogle Scholar
  5. 5.
    M. Darouach, M. Zasadzinski, and M. Boutayeb, Automatica, 39, 867–876 (2003).MATHMathSciNetCrossRefGoogle Scholar
  6. 6.
    D. Janczak and Y. Grishin, Control and Cybernetics, 35 (4), 851–862 (2006).MATHMathSciNetGoogle Scholar
  7. 7.
    S. Gillijns and B. Moor, Automatica, 43, 111–116 (2007).MATHCrossRefGoogle Scholar
  8. 8.
    C.-S. Hsieh, Asian J. Control, 12, No. 4, 510–523 (2010).MathSciNetGoogle Scholar
  9. 9.
    G. M. Koshkin and V. I. Smagin, in: Proc. 10th Int. Conf. on Digital Technologies, Žilina (2014), pp. 120–124.Google Scholar
  10. 10.
    M. Witczak, Fault Diagnosis and Fault-Tolerant Control Strategies for Non-Linear Systems. Lecture Notes in Electrical Engineering, Switzerland, Springer International Publishing, Cham (2014), pp. 19–56.Google Scholar
  11. 11.
    F. Ben Hmida, K. Khemiri, J. Ragot, and M. Gossa, Math. Probl. Eng., 2010, 1–24 (2010).Google Scholar
  12. 12.
    S. V. Smagin, Avtometriya, 45, No. 6, 29–37 (2009).MathSciNetGoogle Scholar
  13. 13.
    V. I. Smagin and S. V. Smagin, Vestn. Tomsk. Gosud. Univ. Upravl., Vychisl. Tekh. i Inform., No. 3(16), 43–51 (2011).Google Scholar
  14. 14.
    V. I. Smagin, Russ. Phys. J., 57, No. 5, 682–690 (2014).CrossRefGoogle Scholar
  15. 15.
    A. A. Amosov and V. V. Kolpakov, Probl. Pered. Inform., No. 1, 3–15 (1972).Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.National Research Tomsk State UniversityTomskRussia

Personalised recommendations