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- W2054930317 abstract "Remote state estimation in networked control systems always consumes too much sensor battery power and communication bandwidth. Under power and communication constraint, we seek a desirable tradeoff between communication rate and estimation performance in terms of estimation error covariance. We propose two data-driven sensor scheduling strategies to achieve that goal. We prove that under our strategies the minimum mean squared error (MMSE) estimator is a Kalmanlike filter which maintains linearity. We give the explicit MMSE estimator under each strategy. In the end we conduct numerical experiment to show the superiority of our design." @default.
- W2054930317 created "2016-06-24" @default.
- W2054930317 creator A5018989058 @default.
- W2054930317 date "2014-12-01" @default.
- W2054930317 modified "2023-10-01" @default.
- W2054930317 title "Data-driven state estimation under limited communication resources" @default.
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- W2054930317 doi "https://doi.org/10.1109/icmic.2014.7020751" @default.
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