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dc.contributor.authorTing, Huan-Chanen_US
dc.contributor.authorChang, Jeang-Linen_US
dc.contributor.authorYeh, Chih-Hueien_US
dc.contributor.authorChen, Yon-Pingen_US
dc.date.accessioned2014-12-08T15:13:27Z-
dc.date.available2014-12-08T15:13:27Z-
dc.date.issued2007-09-01en_US
dc.identifier.issn1562-2479en_US
dc.identifier.urihttp://hdl.handle.net/11536/10402-
dc.description.abstractThis paper presents an advanced GM(1,1) model which can improve the accuracy of the conventional grey prediction and applies it to discrete sliding-mode control (DSMC). Using a Lagrange polynomial to take as a compensator and combining it with the original GM(1,1) model, the proposed prediction method can decrease the prediction error and easily implement in microprocessors with less computing time and memories. Then we employ this technique in DSMC to detect the system unknown perturbation. Comparing with the conventional DSMC, the proposed algorithm can reduce the switching gain and result in that the system state is bounded in a smaller region. Numeric simulation results of a DC motor are given to illustrate the feasibility and successfulness of the proposed design.en_US
dc.language.isoen_USen_US
dc.subjectGM(1,1)en_US
dc.subjectlagrange polynomialen_US
dc.subjectsliding modeen_US
dc.subjectDC motoren_US
dc.titleDiscrete time sliding-mode control design with greyen_US
dc.typeArticleen_US
dc.identifier.journalINTERNATIONAL JOURNAL OF FUZZY SYSTEMSen_US
dc.citation.volume9en_US
dc.citation.issue3en_US
dc.citation.spage179en_US
dc.citation.epage185en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000255333400008-
dc.citation.woscount5-
Appears in Collections:Articles