Design of sampled-data fuzzy-model-based control systems by using intelligent digital redesign

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)22_Publication in policy or professional journal

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Detail(s)

Original languageEnglish
Pages (from-to)509-517
Journal / PublicationIEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume49
Issue number4
Publication statusPublished - Apr 2002

Abstract

In this brief, we develop an intelligent digital redesign method for hybrid state space fuzzy-model-based controllers, effective for stabilization of continuous-time uncertain nonlinear systems under discrete-time controller. Takagi-Sugeno (TS) fuzzy model is used to represent the complex system as multiple and uncertain linear state-space models over different local operating regions. A continuous-time fuzzy-model-based controller is then synthesized for stabilization, where the guaranteed-cost design method is utilized to cope with system uncertainties. The local controllers of the continuous-time fuzzy-model-based controller are then converted to equivalent discrete-time counterparts and aggregated through the fuzzy inference system to give a discrete-time fuzzy-model-based controller. Finally, a TS fuzzy model for the chaotic Lorenz system is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

Research Area(s)

  • Chaotic Lorenz system, Fuzzy-model-based control, Guaranteed-cost control, Intelligent digital redesign, Linear matrix inequality, Sampled-data control

Citation Format(s)

Design of sampled-data fuzzy-model-based control systems by using intelligent digital redesign. / Chang, Wook; Park, Jin Bae; Joo, Young Hoon; Chen, Guanrong.

In: IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, Vol. 49, No. 4, 04.2002, p. 509-517.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)22_Publication in policy or professional journal