TY - JOUR

T1 - Comparison of Parameter Identification Methods for Linear Dynamic Systems Under Mixed Noise

AU - Lomov, A. A.

AU - Fedoseev, A. V.

N1 - Publisher Copyright: © 2021, Springer Science+Business Media, LLC, part of Springer Nature. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/3

Y1 - 2021/3

N2 - We study the possibility of comparing methods with the atypical noise conditions by examing three parameter identification methods and using the sensitivity theory for local expansions of objective functions. The theoretical results are confirmed by numerical experiments on the equations of longitudinal motion of an aircraft, where the parameters are identified by the linear least-squares method, the method of instrumental variables in a frequency domain, and the variational method. The mixed noise (an additive noise in observations and a noise in the residual of the equation) is taken for perturbations.

AB - We study the possibility of comparing methods with the atypical noise conditions by examing three parameter identification methods and using the sensitivity theory for local expansions of objective functions. The theoretical results are confirmed by numerical experiments on the equations of longitudinal motion of an aircraft, where the parameters are identified by the linear least-squares method, the method of instrumental variables in a frequency domain, and the variational method. The mixed noise (an additive noise in observations and a noise in the residual of the equation) is taken for perturbations.

UR - http://www.scopus.com/inward/record.url?scp=85100672603&partnerID=8YFLogxK

U2 - 10.1007/s10958-021-05238-0

DO - 10.1007/s10958-021-05238-0

M3 - Article

AN - SCOPUS:85100672603

VL - 253

SP - 407

EP - 418

JO - Journal of Mathematical Sciences (United States)

JF - Journal of Mathematical Sciences (United States)

SN - 1072-3374

IS - 3

ER -