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Stabilization of Multirate Sampled-Data Fuzzy Systems Based on an Approximate Discrete-Time Model

  • Do Wan Kim
  • Jin Bae Park
  • Young Hoon Joo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)

Abstract

This paper studies a stabilization problem for a multirate digital control of fuzzy systems based on the approximately discretized model. In the multirate control scheme, a numerical integration scheme is used to approximately predict the current state from the state measured at the sampling points. It is shown that the multirate digital fuzzy controller stabilizing an approximate discrete-time fuzzy model would also stabilize the sampled-data fuzzy system in the sufficiently small control update time. Furthermore, some sufficient conditions for the stabilization of the approximate discrete-time fuzzy model are provided under the delta-operator frame work, which are expressed as the linear matrix inequalities (LMIs) and thereby easily tractable by the convex optimization techniques. A numerical example is demonstrated to visualize the feasibility of the developed methodology.

Keywords

Fuzzy System Linear Matrix Inequality Digital Controller Numerical Integration Scheme Longe Sampling Period 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Do Wan Kim
    • 1
  • Jin Bae Park
    • 1
  • Young Hoon Joo
    • 2
  1. 1.Yonsei UniversitySeodaemun-gu, SeoulKorea
  2. 2.Kunsan National UniversityKunsan, ChunbukKorea

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