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This article is cited in 2 scientific papers (total in 2 papers)
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.
Citation:
M. V. Khlebnikov, “A comparison of guaranteeing and Kalman filters”, Avtomat. i Telemekh., 2023, no. 4, 64–95; Autom. Remote Control, 84:4 (2023), 434–459
Linking options:
https://www.mathnet.ru/eng/at16042 https://www.mathnet.ru/eng/at/y2023/i4/p64
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Abstract page: | 86 | References: | 29 | First page: | 18 |
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