NDLI: State reconstruction for linear time-invariant systems with binary-valued output observations

Content Provider	IEEE Xplore Digital Library
Author	Guohua Xu Le Yi Wang Yin, G.G.
Copyright Year	2007
Description	Author affiliation: Wayne State Univ., Detroit (Guohua Xu; Le Yi Wang)
Abstract	This paper studies state reconstruction problems for systems whose outputs are measured only by binary-valued sensors. The traditional passive-type state reconstruction that does not require input design will fail in general, even if the system has a full rank observability matrix. It is shown that under controllability conditions and bounded uncertainty on the initial state, it is always possible to construct a causal input that will cause the output to cross the sensor threshold in a designated time interval. Information on the time instants of threshold crossing is then used to reconstruct the initial state. It is proved that if the system is observable, such a reconstruction is always possible if the eigenvalues of the system are all real valued. If the eigenvalues of the system contain only simple imaginary values, it is sufficient that threshold crossing occurs within a relatively small time interval. In general, an input can be randomized to ensure that the state can be reconstructed with probability one. These results lead to an active state reconstruction algorithm.
Starting Page	4305
Ending Page	4310
File Size	877255
Page Count	6
File Format	PDF
ISBN	9781424414970
ISSN	01912216
DOI	10.1109/CDC.2007.4434116
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Sensor systems Observability Eigenvalues and eigenfunctions Controllability State estimation Control systems Reconstruction algorithms Fault diagnosis Fault detection
Content Type	Text
Resource Type	Article

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