Journal
AUTOMATICA
Volume 122, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2020.109248
Keywords
Unknown exogenous inputs; Event-triggered scheduling; Robust estimation; Risk-sensitive filtering; Remote state estimation
Funding
- Natural Sciences and Engineering Research Council of Canada
- National Natural Science Foundation of China [61973030]
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An event-triggered robust state estimation problem for linear time-varying systems subject to Gaussian noises and non-stochastic unknown exogenous inputs is investigated in this work. To design the estimator, the state estimation problem is formulated as an optimization problem with a risk-sensitive cost function. This problem is solved by constructing a reference probability measure, under which the cost function has a simpler form and an information state can be developed. The obtained robust state estimator is shown to have a recursive form parameterized by a Riccati-type time-varying matrix equation. The effectiveness of the proposed event-based robust state estimator is illustrated with numerical examples. (c) 2020 Elsevier Ltd. All rights reserved.
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