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Journal Dynamics of Complex Systems - XXI century №2 for 2014 г.
Article in number:
Analysis of algorithms parametric identification information-operating systems that meet the principle Hamilton-Ostrogradskii
Keywords:
parametric identification
control system
the principle of Hamilton-Ostrogradskii
recurrence equations
dynamical systems
Authors:
D. S. Andrashitov - Ph.D. (Eng.), Military academy of strategic rocket forces them Peter the Great, Russia
I. V. Deryabkin - Post-graduate Student, South-Russian State University of Economics and Service, Russia, Rostov-on-Don. E-mail: i.deryabkin@jint.biz
A. A. Kostoglotov - Dr.Sc. (Eng.), Professor of Department «Information Technology in service», South-Russian State University of Economics and Service, Russia, Rostov-on-Don. E-mail: kostoglotov@aaanet.ru
S. V. Lazarenko - Ph.D. (Eng.), Senior Lecturer of Department «Electronics», South-Russian State University of Economics and Service, Russia, Rostov-on-Don. E-mail: rh3311@mail.ru
I. V. Deryabkin - Post-graduate Student, South-Russian State University of Economics and Service, Russia, Rostov-on-Don. E-mail: i.deryabkin@jint.biz
A. A. Kostoglotov - Dr.Sc. (Eng.), Professor of Department «Information Technology in service», South-Russian State University of Economics and Service, Russia, Rostov-on-Don. E-mail: kostoglotov@aaanet.ru
S. V. Lazarenko - Ph.D. (Eng.), Senior Lecturer of Department «Electronics», South-Russian State University of Economics and Service, Russia, Rostov-on-Don. E-mail: rh3311@mail.ru
Abstract:
This paper presents two methods for multi-parameter identification using the combined maximum principle, taking into account the physical characteristics of the systems in the form of the variational principle of Hamilton-Ostrogradskii. On this basis, synthesized resistant to noise measurements identification algorithms are characterized by high accuracy of the parameter estimates and their rate of convergence to the actual values. This is confirmed by the results of mathematical modeling of the pressure sensor parameter identification information management system in comparison with the Kalman filter.
Pages: 90-95
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