Design of T-S fuzzy classifier via linear matrix inequality approach

Abstract

A linear matrix inequality approach to designing accurate classifier with a compact T-S(Takagi-Sugeno) fuzzy-rule is proposed, in which all the elements of the T-S fuzzy classifier design problem have been moved in parameters of a LMI optimization problem. Two-step procedure is used to effectively design the T-S fuzzy classifier with many tuning parameters: antecedent part and consequent part design. Then two LMI optimization problems are formulated in both parts and solved efficiently by using interior-point method. Iris data is used to evaluate the performance of the proposed approach. From the simulation results, the proposed approach showed superior performance over other approaches. © Springer-Verlag Berlin Heidelberg 2005.