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Feed forward filters for state and disturbance estimation

Authors: Aaron Radke; Robert Miklosovic; Brian Fast;

Feed forward filters for state and disturbance estimation

Abstract

This paper introduces a method for representing an observer as a set of decoupled filters to provide an understanding of observer design for the practitioner. The concept uses feed forward information to predict and cancel phase lag inherent in common filters. A general modeling paradigm is also proposed to simplify disturbance rejection techniques. Both ideas are applied to analyze and compare approximate differentiators, state observers, disturbance observers (DOB), unknown input observers (UIO), and extended state observers (ESO).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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