In this article we found the solution of fuzzy linear controlled systemwith fuzzy initial conditions by using -cuts and presentation of numbersin a more compact form by moving to the eld of complex numbers. Next, afuzzy optimal control problem for a fuzzy system is considered to optimize theexpected value of a fuzzy objective function. Based on Pontryagin MaximumPrinciple, a constructive equati...

In paper the fuzzy linear system d x C x A ~ ~ ~   where A and C are crisp matrices and n m  d~ is a LR fuzzy numbers vector, is investigated in detail. We generalize the definition and arithmetic operations of LR fuzzy numbers and convert the dual fuzzy linear system to two crisp systems of linear equations. Then the minimal fuzzy solution of the original fuzzy system is obtained by solving...

In this paper, the synchronization of a new hyperchaotic complex system based on T-S fuzzy model is proposed. First, the considered hyperchaotic system is represented by T-S fuzzy model equivalently. Then, by using the parallel distributed compensation (PDC) method and by applying linear system theory and exact linearization (EL) technique, a fuzzy controller is designed to realize the synchron...

in this paper, a  fuzzy numerical procedure for solving fuzzy linear volterra integro-differential equations of the second kind under strong  generalized differentiability is designed. unlike the existing numerical methods, we do not replace the original fuzzy equation by a $2times 2$ system ofcrisp equations, that is the main difference between our method  and other numerical methods.error ana...

This paper presents a novel adaptive neuro-fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part. The capability of the proposed ANFIS2 for function approximation and dynamical system identification is remarkable. The structure of ANFIS2 is very sim...

In this article, an effective method to control a power system during emergency conditions is presented. Based on Fuzzy Linear Programming (FLP), a new technique is developed to solve the Load Shedding and Generation Reallocation (LSGR) optimization Problem. The objective function consists of terms of load curtailments and deviations in generation schedules. The constraints are power system var...

the fuzzy linear regression model with fuzzy input-output data andcrisp coefficients is studied in this paper. a linear programmingmodel based on goal programming is proposed to calculate theregression coefficients. in contrast with most of the previous works, theproposed model takes into account the centers of fuzzy data as animportant feature as well as their spreads in the procedure ofconstr...

ABSTRACT: In this study, adaptive neuro-fuzzy inference system, and feed forward neural network as two artificial intelligence-based models along with conventional multiple linear regression model were used to predict the multi-station modelling of dissolve oxygen concentration at the downstream of Mathura City in India. The data used are dissolved oxygen, pH, biological oxygen demand and water...

In this article, an effective method to control a power system during emergency conditions is presented. Based on Fuzzy Linear Programming (FLP), a new technique is developed to solve the Load Shedding and Generation Reallocation (LSGR) optimization Problem. The objective function consists of terms of load curtailments and deviations in generation schedules. The constraints are power system var...

In this work, we propose an approach for computing the positive solution of a fully fuzzy linear system where the coefficient matrix is a fuzzy n×n matrix. To do this, we use arithmetic operations on fuzzy numbers that introduced by Kaffman in [18] and convert the fully fuzzy linear system into two n× n and 2n× 2n crisp linear systems. If the solutions of these linear systems don’t satisfy in p...