E3S Web Conf.
Volume 210, 2020Innovative Technologies in Science and Education (ITSE-2020)
|Number of page(s)||11|
|Published online||04 December 2020|
Quasi-optimal synthesis of an adaptive filter in the problem of estimating the state of dynamic systems
1 Rostov State Transport University, 344038, Rostovskogo Strelkovogo Polka Narodnogo Opolcheniya Sq., 2, Rostov-on-Don, Russia
2 Don State Technical University, 344003, Gagarin sq., 1, Rostov-on-Don, Russia
* Corresponding author: email@example.com
The problem of synthesis of filters to estimate the state of dynamical systems is considered based on the condition for the maximum of the generalized power function and stationarity of the generalized Lagrangian and Hamiltonian of the estimated system model. The paper demonstrates that the use of invariants in combination with the decomposition principle makes it possible to simplify the equations of controlled motion and reduce them to a system of independent equations in terms of the number of degrees of freedom. This approach reduces the number of unknown parameters of the motion model, which greatly simplifies the adaptation process when developing filters for quasi-optimal estimation of the state parameters of dynamic systems. Comparative analysis of the results of the mathematical simulation shows that the application of the proposed method increases the efficiency of filters of the Kalman structure.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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