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dc.contributor.authorHagiwara, Tomomichi-
dc.contributor.authorKim, Jung Hoon-
dc.date.accessioned2024-01-19T11:06:58Z-
dc.date.available2024-01-19T11:06:58Z-
dc.date.created2022-02-28-
dc.date.issued2017-12-
dc.identifier.issn0743-1546-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/114601-
dc.description.abstractThis paper is concerned with linear time-invariant (LTI) sampled-data systems together with their yet another H-2 norm introduced recently as an alternative to the two well-known definitions. Taking account of the linear periodically time-varying nature of LTI sampled-data systems, this norm is defined as the supremum of the L-2 norms of all the tau-dependent responses for the impulse inputs occurring at the instant tau in the sampling interval [0, h). We first review the closed-form expression of this new H-2 norm derived through the lifted representation of LTI sampled-data systems. We next develop a discretization method of the continuous-time generalized plant, by which the new H-2 norm of LTI sampled-data systems can be characterized by using the discrete-time H-2 norm. We then reinterpret the closed-form expression of the H-2 norm, and derive a computable upper bound together with a lower bound of the norm. We further show that the gap between the upper and lower bounds converges to 0 at the rate of 1/N, where N is the gridding approximation parameter. Finally, a numerical example is given to demonstrate the effectiveness of the computation method.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleA Discretization Approach to the Analysis of Yet Another H-2 Norm of LTI Sampled-Data Systems-
dc.typeConference-
dc.description.journalClass1-
dc.identifier.bibliographicCitation56th Annual IEEE Conference on Decision and Control (CDC)-
dc.citation.title56th Annual IEEE Conference on Decision and Control (CDC)-
dc.citation.conferencePlaceUS-
dc.citation.conferencePlaceMelbourne, AUSTRALIA-
dc.citation.conferenceDate2017-12-12-
dc.relation.isPartOf2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC)-
dc.identifier.wosid000424696903078-
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KIST Conference Paper > 2017
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