New Discrete Tanaka Sugeno Kang Fuzzy Systems Characterization and Stability Domain

Authors

  • Mohamed BENREJEB Ecole Nationale d’Ingénieurs de Tunis Unité de Recherche LARA-Automatique BP 37, Le Belvédí¨re, 1002 Tunis, Tunisie
  • Dhaou SOUDANI Ecole Nationale d’Ingénieurs de Tunis Unité de Recherche LARA-Automatique BP 37, Le Belvédí¨re, 1002 Tunis, Tunisie
  • Anis SAKLY Ecole Nationale d’Ingénieurs de Tunis Unité de Recherche LARA-Automatique BP 37, Le Belvédí¨re, 1002 Tunis, Tunisie
  • Pierre BORNE Ecole Centrale de Lille, Cité scientifique Laboratoire d’Automatique, Génie Informatique et Signal BP 48, 59651 Villeneuve d’Ascq Cedex, France

Keywords:

Discrete nonlinear systems, discrete TSK fuzzy model, t-norm, stability domain, vector norm, arrow form matrix

Abstract

In this paper, an analytical approach to characterize discrete Tanaka Sugeno Kang (TSK) fuzzy systems is presented. This characterization concerns the choice of the adequate conjunctive operator between input variables of discrete TSK fuzzy models, t-norm, and its impact on stability domain estimation. This new approach is based on stability conditions issued from vector norms corresponding to a vector-Lyapunov function. In particular, second order discrete TSK models are considered and this work concludes that Zadeh’s t-norm, logic product min, gives the largest estimation of stability domain.

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Published

2006-10-01

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