The paper deals with the problem of synthesis of a controller to the plant described by Takagi-Sugeno fuzzy model with linear input-output submodels in the consequents of rules. A procedure for design of the controller guaranteeing stability of closed-loop system based on polynomial approach is presented. The controller assignes the same characteristic polynomial for all feasible linear subsyst...

The dynamic fuzzy logic system (DFLS) consists of static fuzzy logic system added with a dynamic element—the integrator—with a feedback constant α. It was shown to possess the important universal approximation capability. Further, Lee and Vukovich developed DFLS based stable indirect adaptive control scheme via Lyapunov synthesis approach for a class of non-linear systems of the form x = f(X) +...

the linear system of equations ax = b where a = [aij ] in cn.n is a crispsingular matrix and the right-hand side is a fuzzy vector is called a singularfuzzy linear system of equations. in this paper, solving singular fuzzy linearsystems of equations using generalized inverses such as drazin inverse andpseudo-inverse are investigated.

the sst decomposition method for solving system of linear equations make it possible to obtain the values of roots of the system with the specified accuracy as the limit of the sequence of some vectors. in this topic we are going to consider vectors as fuzzy vectors. we have considered a numerical example and tried to find out solution vector x in fuzzified form using method of sst decomposition.

AX B In the paper, a class of fuzzy matrix equations    B where A is an m × n crisp matrix and is an m × p arbitrary LR fuzzy numbers matrix, is investigated. We convert the fuzzy matrix equation into two crisp matrix equations. Then the fuzzy approximate solution of the fuzzy matrix equation is obtained by solving two crisp matrix equations. The existence condition of the strong LR fuzzy s...

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...

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 ...

The SST Decomposition Method for solving system of linear equations make it possible to obtain the values of roots of the system with the specified accuracy as the limit of the sequence of some vectors. In this topic we are going to consider vectors as fuzzy vectors. We have considered a numerical example and tried to find out solution vector x̃ in fuzzified form using method of SST Decomposition.