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JOURNALS // Siberian Journal of Pure and Applied Mathematics // Archive

Sib. J. Pure and Appl. Math., 2018 Volume 18, Issue 3, Pages 45–59 (Mi vngu478)

This article is cited in 3 papers

Comparison of the methods of parametric identification of linear dynamical systems under mixed noise

A. A. Lomovab, A. V. Fedoseevba

a Sobolev Institute of Mathematics SB RAS, 4, Akad. Koptyuga pr., Novosibirsk 630090, Russia
b Novosibirsk State University, 1, Pirogova St., Novosibirsk 630090, Russia

Abstract: In the article we study the possibility of comparison of parametric identification methods by the sensitivity theory via local expansions of the objective functions using as an example three identification methods. The theoretical results are verified by computational identification of the equations of longitudinal motion of the aircraft which parameters are identified by a) the linear least-squares method, b) the method of instrumental variables in frequency domain, c) the variational method (closely related to the STLS and GTLS methods). The simulation used a mixed additive noise: in the observations and in the residuals of the model equations.

Keywords: linear dynamic systems, parameter identification, sensitivity functions, mixed noise.

UDC: 681.5.015

Received: 10.04.2018

DOI: 10.33048/pam.2018.18.305


 English version:
Journal of Mathematical Sciences, 2021, 253:4, 407–418


© Steklov Math. Inst. of RAS, 2024