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An unscented Kalman filter is used for state estimation.
Kalman filter and its variants have been used for state estimation of systems described by ordinary differential equation (ODE) models.
Kalman filters and open-loop observers are used for state estimation and residual generation based on the resulting linear models.
Our robust admissibility analysis result, which can be directly used for state estimation, cannot be so for state-feedback control design.
A sliding mode observer is used for state estimation and the resulting nonlinear controller observer pair is implemented on an engine test facility.
When only two on-line measurements of reaction variables are used for state estimation, the prediction of reaction rates and product concentrations are unsatisfactory.
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The greater in magnitude covariate coefficients and higher odds ratios are explained by the linear system model the Kalman filter uses for state estimation.
It directly approximates the covariance matrix and is, in this context, used just for state estimation.
EnKFs can also be used for state-parameter estimation, using the so-called "Joint-EnKF" approach.
This framework is designed to offer an easy to use tool for state estimation of discrete time dynamic stochastic systems.
The designed observer provides estimation of the state, which converges asymptotically to the actual state, and is then used for state feedback control.
More suggestions(15)
used for engineering estimation
used for variance estimation
used for model estimation
used for state licensure
used for parameter estimation
used for state state-space
used for eBV estimation
used for state business
used for protein estimation
used for state matching
used for damage estimation
used for consumption estimation
used for state infrastructure
used for risk estimation
used for state state-of-the-art
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