Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/3311
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dc.contributor.authorSun, Yalei.en_US
dc.date.accessioned2008-09-17T09:27:08Z-
dc.date.available2008-09-17T09:27:08Z-
dc.date.copyright2003en_US
dc.date.issued2003-
dc.identifier.urihttp://hdl.handle.net/10356/3311-
dc.description.abstractThe theme of this research focuses on design, analysis and applications of a new type of hybrid fuzzy controllers for nonlinear systems. Since nonlinearities present in real-life systems are very complicated and cannot be modeled accurately, fuzzy controllers that employ fuzzy logic to make control decisions are widely adopted to exploit the tolerance for imprecision, uncertainty, partial truth and approximation in control systems. When fuzzy controllers are used together with conventional control methods, the resulting controllers are often called hybrid fuzzy controllers. Fuzzy logic is just one constituent of soft computing methods. Since the central tenet of the soft computing methods is that the constituents are complementary rather than competitive, another principal member of soft computing methods, termed evolutionary algorithms, is adopted to allow the design of hybrid fuzzy controllers to be carried out optimally.en_US
dc.rightsNanyang Technological Universityen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation-
dc.titleOptimal design of hybrid fuzzy controllers for nonlinear systemsen_US
dc.typeThesisen_US
dc.contributor.supervisorEr, Meng Jooen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeDoctor of Philosophy (EEE)en_US
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