Suboptimal parametric identification of nonlinear stochastic systems

Authors

  • V. I. Mamai Rostov-on-Don Military Institute of the Rocket Troops, Russian Federation
  • A. V. Sotnikov Rostov-on-Don Military Institute of the Rocket Troops, Russian Federation
  • O. G. Shcherban' Rostov-on-Don Military Institute of the Rocket Troops, Russian Federation

DOI:

https://doi.org/10.3103/S0735272705030027

Abstract

The problem of parametric identification of stochastic nonlinear systems is resolved based on the use of generalized probabilistic criteria. This approach allows for a potentially better accuracy of the estimation-identification procedure as compared with traditional methods, and shows independence of computational expenditures on the dimension of the vector of unknown parameters.

References

KRASOVSKII, A. (ed.). Handbook of the Automatic Control Theory [in Russian]. Moscow: Nauka, 1987.

SAGE, A.P.; MELSA, J.L. System Identification. New York-London: Academic Press, 1971.

KAZAKOV, I.Y. Statistical Theory of Control Systems in State Space [in Russian]. Moscow: Nauka, 1975.

CHERNOV, A.A.; YASTREBOV, V.D. Izv. RAN. Kosmicheskiye Issledovaniya, v.22, n.3, p.361-368, 1984.

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Published

2005-03-02

Issue

Vol. 48 No. 3 (2005): Military Radioelectronic Technologies

Section

Research Articles