This paper examines the problem of designing robust H∞ controllers for for HIV/AIDS infection system with dual drug dosages described by a Takagi-Sugeno (TS) fuzzy model. Based on a linear matrix inequality (LMI) approach, we develop an H∞ controller which guarantees the L2-gain of the mapping from the exogenous input noise to the regulated output to be less than some prescribed value for the s...

in this paper, a numerical method for nding minimal solution of a mn fullyfuzzy linear system of the form ax = b based on pseudo inverse calculation,is given when the central matrix of coecients is row full rank or column fullrank, and where a~ is a non-negative fuzzy mn matrix, the unknown vectorx is a vector consisting of n non-negative fuzzy numbers and the constant b isa vector consisti...

A dual for linear programming problems with fuzzy parameters is introduced and it is shown that a two person zero sum matrix game with fuzzy pay-o(s is equivalent to a primal-dual pair of such fuzzy linear programming problems. Further certain di6culties with similar studies reported in the literature are discussed.

A dual for linear programming problems with fuzzy parameters is introduced and it is shown that a two person zero sum matrix game with fuzzy pay-o(s is equivalent to a primal–dual pair of such fuzzy linear programming problems. Further certain di6culties with similar studies reported in the literature are discussed. c © 2003 Elsevier B.V. All rights reserved.

different methods have been proposed for finding the non-negative solution of fully fuzzy linear system (ffls) i.e. fuzzy linear system with fuzzy coefficients involving fuzzy variables. to the best of our knowledge, there is no method in the literature for finding the non-negative solution of a ffls without any restriction on the coefficient matrix. in this paper a new computational method is ...

in this paper, we present gauss-sidel and successive over relaxation (sor) iterative methods for finding the approximate solution system of fuzzy sylvester equations (sfse), ax + xb = c, where a and b are two m*m crisp matrices, c is an m*m fuzzy matrix and x is an m*m unknown matrix. finally, the proposed iterative methods are illustrated by solving one example.

Dual-mode fuzzy dynamic matrix control (fuzzy DMC-FDMC) algorithms with guaranteed nominal stability for constrained nonlinear plants are presented. The algorithms join the advantages of fuzzy Takagi-Sugeno modeling and the predictive dual-mode approach in a computationally efficient version. Thus, they can bring an improvement in control quality compared with predictive controllers based on li...

Different methods have been proposed for finding the non-negative solution of fully fuzzy linear system (FFLS) i.e. fuzzy linear system with fuzzy coefficients involving fuzzy variables. To the best of our knowledge, there is no method in the literature for finding the non-negative solution of a FFLS without any restriction on the coefficient matrix. In this paper a new computational method is ...

In this work, we propose an approach for computing the compromised solution of an LR fuzzy linear system by using of a ranking function when the coefficient matrix is a crisp mn matrix. To do this, we use expected interval to find an LR fuzzy vector, X , such that the vector (AX ) has the least distance from (b) in 1 norm and the 1 cut of X satisfies the crisp linear system AX = b ...

This paper analyzes a linear system of equations when the righthandside is a fuzzy vector and the coefficient matrix is a crisp M-matrix. Thefuzzy linear system (FLS) is converted to the equivalent crisp system withcoefficient matrix of dimension 2n × 2n. However, solving this crisp system isdifficult for large n because of dimensionality problems . It is shown that thisdifficulty may be avoide...