Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/54191
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dc.titleA general fuzzy control scheme for nonlinear processes with stability analysis
dc.contributor.authorChai, J.-S.
dc.contributor.authorTan, S.
dc.contributor.authorChen, Q.
dc.contributor.authorHang, C.-C.
dc.date.accessioned2014-06-16T09:28:32Z
dc.date.available2014-06-16T09:28:32Z
dc.date.issued1998
dc.identifier.citationChai, J.-S.,Tan, S.,Chen, Q.,Hang, C.-C. (1998). A general fuzzy control scheme for nonlinear processes with stability analysis. Fuzzy Sets and Systems 100 (1-3) : 179-195. ScholarBank@NUS Repository.
dc.identifier.issn01650114
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/54191
dc.description.abstractIn this paper we develop a general fuzzy control scheme for nonlinear processes. Assuming little knowledge about the dynamics of the controlled process, the proposed scheme starts by probing the process at different points in its operating region to generate a fuzzy quantisation. A simple local controller is then designed at each fuzzy locality. A fuzzy inference mechanism then links up the local controllers to form a global controller which can be further refined by the learning algorithm. By employing a newly developed structure-adaptive fuzzy modelling scheme, the appropriate fuzzy rule-base for the inference mechanism can be extracted stably and efficiently. The conditions for the stability of the global controller are rigourously established. Simulation results are presented to illustrate the effectiveness of the scheme. © 1998 Elsevier Science B.V. All rights reserved.
dc.sourceScopus
dc.subjectAdaptive systems
dc.subjectFuzzy modelling
dc.subjectNonlinear control
dc.subjectSugeno fuzzy model
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.sourcetitleFuzzy Sets and Systems
dc.description.volume100
dc.description.issue1-3
dc.description.page179-195
dc.description.codenFSSYD
dc.identifier.isiutNOT_IN_WOS
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