NDLI: Dead-beat estimation problems for 2D behaviors

Content Provider	Springer Nature Link
Author	Bisiacco, Mauro Valcher, Maria Elena
Copyright Year	2007
Abstract	In this paper we address the dead-beat estimation problem for the class of two-dimensional (2D) behaviors which are described by means of a 2D difference equation, and whose trajectories evolutions pertain the “nonnegative half-plane”. For this class of behaviors, the concept of nilpotency is defined and fully characterized. After this preliminary step, the estimation problem is formally addressed. Indeed, the concept of (consistent or not) 2D dead-beat observer (DBO) of the system relevant variables from the system measured variables is introduced, and a set of necessary and sufficient conditions for the existence of such a DBO is given. Finally, a complete parametrization of the family of all consistent DBOs is given, and some partial results, together with an interesting counterexample, regarding the class of (not necessarily consistent) DBOs are presented. To conclude the paper, the general dead-beat estimation theory developed in this paper is adjusted to address and solve several problems, like state estimation, the design of unknown input observers or the design of fault detectors and identifiers (possibly in the presence of disturbances), for 2D systems described by quarter-plane causal 2D state space models.
Starting Page	287
Ending Page	306
Page Count	20
File Format	PDF
ISSN	09236082
Journal	Multidimensional Systems and Signal Processing
Volume Number	19
Issue Number	3-4
e-ISSN	15730824
Language	English
Publisher	Springer US
Publisher Date	2007-12-06
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Two-dimensional (2D) behaviors/state space models Nilpotent 2D behaviors Dead-beat observers $$\mathcal {H}_0$$ -polynomials Artificial Intelligence (incl. Robotics) Signal, Image and Speech Processing Electronic and Computer Engineering Circuits and Systems
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Signal Processing Information Systems Computer Science Applications Software Hardware and Architecture

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