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Adaptive identification as gain scheduling

Authors: Ryo Watanabe; Kenko Uchida;

Adaptive identification as gain scheduling

Abstract

We consider the Lyapunov approach to adaptive identification for systems with unknown time invariant parameter. We describe the adaptive identification problem as stability analysis for a linear parameter varying system, and then discuss the convergence of identification error and its convergence rate based on a parameter dependent Lyapunov function.

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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!
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Average
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