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Automation and Remote Control

Erschienen in:

01.04.2023 | STOCHASTIC SYSTEMS

A Comparison of Guaranteeing and Kalman Filters

verfasst von: M. V. Khlebnikov

Erschienen in: Automation and Remote Control | Ausgabe 4/2023

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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.

Vorheriger Artikel Optimal Recovery of a Square Integrable Function from Its Observations with Gaussian Errors

Nächster Artikel Optimization of the Cluster-Variant Method of Constructing a Multi-Position Direction Finding System for Conditions of a Priori Uncertainty

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Titel: A Comparison of Guaranteeing and Kalman Filters
verfasst von: M. V. Khlebnikov
Publikationsdatum: 01.04.2023
Verlag: Pleiades Publishing
Erschienen in: Automation and Remote Control / Ausgabe 4/2023
Print ISSN: 0005-1179
Elektronische ISSN: 1608-3032
DOI: https://doi.org/10.1134/S0005117923040094

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