2009
DOI: 10.3166/ejc.15.194-204
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Discrete-time Normal Form for Left Invertibility Problem

Abstract: This paper deals with the design of quadratic and higher order normal forms for the left invertibility problem. The linearly observable case and one-dimensional linearly unobservable case are investigated. The interest of such a study in the design of a delayed discrete-time observer is examined. The example of the Burgers map with unknown input is treated and a delayed discrete-time observer is designed. Finally, some simulated results are commented.

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Cited by 15 publications
(13 citation statements)
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“…For the reception, based on the works of Belmouhoub et al [24] and Djemaï et al [25], we design a delayed discrete observer for System (2) with sampling period T . In the following, some results on a delayed discrete observer are given.…”
Section: Presentation Of the Receivermentioning
confidence: 99%
“…For the reception, based on the works of Belmouhoub et al [24] and Djemaï et al [25], we design a delayed discrete observer for System (2) with sampling period T . In the following, some results on a delayed discrete observer are given.…”
Section: Presentation Of the Receivermentioning
confidence: 99%
“…The master system is modelled as follows: [24][25]. By referring to the inclusion method [26][27], the considered hyperchaotic master system (1) …”
Section: Main Methodologymentioning
confidence: 99%
“…The hyperchaotic attractors of master system (26) and slave system (27), Figure 2, with the initial values Let us consider the following master and slave BaierKlein and Hitzel-Zele hyperchatic systems [18,[24][25]: the master system: …”
Section: Synchronization Of Two Non-identical Discrete-time Hypementioning
confidence: 99%
“…For the reception, based on the works of [24][25], we have designed a delayed discrete observer that works with a sampling time T and which allows to reconstruct all states and the transmitted message m of (5). The design of the observer is detailed in the work [26], it is given as follow: …”
Section: A Chaotic Observermentioning
confidence: 99%