Online State Estimation for Time-Varying Systems
نویسندگان
چکیده
The article investigates the problem of estimating state a time-varying system with linear measurement model; in particular, considers case where number measurements available can be smaller than states. In lieu batch least-squares approach—well-suited for static networks, sufficient could collected to obtain full-rank design matrix—the proposes an online algorithm estimate possibly by processing as and when available. hinges on generalized cost augmented proximal-point-type regularization. With solution regularized closed-form, is written dynamical updated based previous new measurements. Conditions under which algorithmic steps are fact contractive mapping shown, bounds estimation error derived different noise models. Numerical simulations provided corroborate analytical findings.
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ژورنال
عنوان ژورنال: IEEE Transactions on Automatic Control
سال: 2022
ISSN: ['0018-9286', '1558-2523', '2334-3303']
DOI: https://doi.org/10.1109/tac.2021.3120679