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JOURNALS // Avtomatika i Telemekhanika // Archive

Avtomat. i Telemekh., 2023 Issue 4, Pages 64–95 (Mi at16042)

This article is cited in 1 paper

Stochastic Systems

A comparison of guaranteeing and Kalman filters

M. V. Khlebnikovab

a Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia
b Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia

Abstract: We propose a new approach to filtering under arbitrary bounded exogenous disturbances based on reducing this problem to an optimization problem. The approach has a low computational complexity since only Lyapunov equations are solved at each iteration. At the same time, it possesses advantages essential from an engineering-practical point of view, namely, the possibilities to limit the filter matrix and to construct optimal filter matrices separately for each coordinate of the system’s state vector. A gradient method for finding the filter matrix is presented. According to the examples, the proposed recurrence procedure is rather effective and yields quite satisfactory results. This paper continues the series of research works devoted to feedback control design from an optimization perspective.

Keywords: linear system, exogenous disturbances, filtering, Kalman filter, Luenberger observer, optimization, Lyapunov equation, gradient method, Newton’s method, convergence.

Presented by the member of Editorial Board: E. Ya. Rubinovich

Received: 23.09.2022
Revised: 21.12.2022
Accepted: 29.12.2022

DOI: 10.31857/S0005231023040050


 English version:
Automation and Remote Control, 2023, 84:4, 434–459


© Steklov Math. Inst. of RAS, 2024