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In this paper, we study the existence, asymptotic behavior of the positive solutions of a fuzzy nonlinear difference equation$$ x_{n+1}=frac{Ax_n+x_{n-1}}{B+x_{n-1}}, n=0,1,cdots,$$ where $(x_n)$ is a sequence of positive fuzzy number, $A, B$ are positive fuzzy numbers and the initial conditions $x_{-1}, x_0$ are positive fuzzy numbers.

The generalized fuzzy valued $theta$-Choquet integrals will beestablished for the given $mu$-integrable fuzzy valued functionson a general fuzzy measure space, and the convergence theorems ofthis kind of fuzzy valued integral are being discussed.Furthermore, the whole of integrals is regarded as a fuzzy valuedset function on measurable space, the double-null asymptoticadditivity and pseudo-double-null asymptotic additivity of thefuzzy valued set functions formed are studied when the fuzzymeasure satisfies autocontinuity from above (below).\

In this study, the roll, yaw and depth fuzzy control of an Au- tonomous Underwater Vehicle (AUV) are addressed. Yaw and roll angles are regulated only using their errors and rates, but due to the complexity of depth dynamic channel, additional pitch rate quantity is used to improve the depth loop performance. The discussed AUV has four aps at the rear of the vehicle as actuators. Two rule bases and membership functions based on Mamdani type and Sugeno type fuzzy rule have been chosen in each loop. By invoking the normalized steepest descent optimization method, the optimum values for the membership function parameters are found. Though the AUV is a highly nonlinear system, the simulation of the designed fuzzy logic control system based on the equations of motion shows desirable behavior of the AUV spe- cially when the parameters of the fuzzy membership functions are optimized.

This paper focuses on the non-fragile guaranteed cost control problem for a class of T-S fuzzy time-varying delay systems with local bilinear models. The objective is to design a non-fragile guaranteed cost state feedback controller via the parallel distributed compensation (PDC) approach such that the closed-loop system is delay-dependent asymptotically stable and the closed-loop performance is no more than a certain upper bound in the presence of the additive controller gain perturbations. A sufficient condition for the existence of such non-fragile guaranteed cost controllers is derived via the linear matrix inequality (LMI) approach and the design problem of the fuzzy controller is formulated in term of LMIs. The simulation examples show that the proposed approach is effective.

In this study we introduce the concepts of statistical convergence of order$beta$ and strong $p-$Ces`{a}ro summability of order $beta$ for sequencesof fuzzy numbers. Also, we give some relations between the statisticalconvergence of order $beta$ and strong $p-$Ces`{a}ro summability of order$beta$ and construct some interesting examples.

This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the La- grangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting the optimal value of the smoothing param- eter is fuzzi ed to t the presented model. Some simulation experiments are then presented which indicate the performance of the proposed method.

In this paper, the problems of robust stabilization and$H_{infty}$ control for uncertain stochastic systems withmultiple time delays represented by the Takagi-Sugeno (T-S) fuzzymodel have been studied. By constructing a new Lyapunov-Krasovskiifunctional (LKF) and using the bounding techniques, sufficientconditions for the delay-dependent robust stabilization and $H_{infty}$ control scheme are presented in terms of linear matrixinequalities (LMIs). By solving these LMIs, a desired fuzzycontroller can be obtained which can be easily calculated byMatlab LMI control toolbox. Finally, a numerical simulation isgiven to illustrate the effectiveness of the proposed method.

An orthogonal approach to the fuzzification of both multisets and hybridsets is presented. In particular, we introduce $L$-multi-fuzzy and$L$-fuzzy hybrid sets, which are general enough and in spirit with thebasic concepts of fuzzy set theory. In addition, we study the properties ofthese structures. Also, the usefulness of these structures is examined inthe framework of mechanical multiset processing. More specifically, weintroduce a variant of fuzzy P~systems and, since simplefuzzy membrane systems have been introduced elsewhere, we simply extendpreviously stated results and ideas.

The paper is concerned with robust stability criteria for Takagi- Sugeno (T-S) fuzzy systems with distributed delays and time delay in the leakage term. By exploiting a model transformation, the system is converted to one of the neutral delay system. Global robust stability result is proposed by a new Lyapunov-Krasovskii functional which takes into account the range of delay and by making use of some inequality techniques. Based on the interval time-varying delays, new stability criteria are obtained in terms of linear matrix inequalities (LMIs). Finally, three numerical examples and their simulations are given to show the effectiveness and advantages of our results.

Based on a complete Heyting algebra, we modify the definition oflattice-valued fuzzifying convergence space using fuzzy inclusionorder and construct in this way a Cartesian-closed category, calledthe category of $L-$ordered fuzzifying convergence spaces, in whichthe category of $L-$fuzzifying topological spaces can be embedded.In addition, two new categories are introduced, which are called thecategory of principal $L-$ordered fuzzifying convergence spaces andthat of topological $L-$ordered fuzzifying convergence spaces, andit is shown that they are isomorphic to the category of$L-$fuzzifying neighborhood spaces and that of $L-$fuzzifyingtopological spaces respectively.

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