Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/51220
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dc.titleNeuro-fuzzy system based identification method for hammerstein processes
dc.contributor.authorJia, L.
dc.contributor.authorChiu, M.-S.
dc.contributor.authorGe, S.S.
dc.date.accessioned2014-04-24T08:36:48Z
dc.date.available2014-04-24T08:36:48Z
dc.date.issued2004
dc.identifier.citationJia, L.,Chiu, M.-S.,Ge, S.S. (2004). Neuro-fuzzy system based identification method for hammerstein processes. 2004 5th Asian Control Conference 1 : 104-111. ScholarBank@NUS Repository.
dc.identifier.isbn0780388739
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/51220
dc.description.abstractHammerstein model, which consists of the cascade structure of a static nonlinearity followed by a linear dynamic part, can effectively describe the nonlinear dynamics of many industrial processes. To circumvent the open problems in existing identification methods of Hammerstein processes, Sung developed a new system identification method, which completely separates the identification problem of the linear dynamic part from that of nonlinear static part using a special test signal. However, the polynomials are employed to approximate the nonlinear static function with some conditions that may limit its practical applications. To alleviate this problem, neuro-fuzzy system is employed in this paper to describe the nonlinear static function of the Hammerstein model without any prior knowledge and restriction on static nonlinear function. Further-more, a non-iterative algorithm is proposed to obtain the neuro-fuzzy system based nonlinear static model. Literature examples are used to illustrate the performance and applicability of the proposed Hammerstein model.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCHEMICAL & BIOMOLECULAR ENGINEERING
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitle2004 5th Asian Control Conference
dc.description.volume1
dc.description.page104-111
dc.identifier.isiutNOT_IN_WOS
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