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• W1551038862 abstract "The paper is concerned with state predictors that include a disturbance dynamics capable of estimating the disturbance to be rejected. The disturbance dynamics is driven by an unknown input signal, the uncertainty input, which is the output of a dynamic feedback driven by the model error (plant minus model output). As an extension of classical observers, the paper shows the advantage of designing a dynamic feedback. A dynamic feedback can be designed to fit the structure of the uncertainty and has the advantage of increasing the relative degree of the state-predictor transfer function, without penalizing the sensitivity itself. A higher relative degree increases the high-frequency rejection rate, thus impeding neglected dynamics components of spilling through control signals to the detriment of stability. A simulated case study shows the better performance of dynamic estimators." @default.
• W1551038862 created "2016-06-24" @default.
• W1551038862 creator A5073039630 @default.
• W1551038862 date "2015-07-01" @default.
• W1551038862 modified "2023-09-26" @default.
• W1551038862 title "On dynamic uncertainty estimators" @default.
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• W1551038862 doi "https://doi.org/10.1109/acc.2015.7171949" @default.
• W1551038862 hasPublicationYear "2015" @default.
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