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This article is cited in 9 scientific papers (total in 9 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), 389–411
Linking options:
https://www.mathnet.ru/eng/at16042 https://www.mathnet.ru/eng/at/y2023/i4/p64
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