a mobile manipulator robot is known as a complex system due to some properties such as coupling between the manipulator and mobile chassis, holonomic and nonholonomic constraints, multivariable and nonlinear dynamics. the control of robot faces the external disturbance, parametric uncertainty and unmodeled dynamics. therefore, the use of an adaptive fuzzy system is suggested for its capability ...

the aim of this paper is to introduce and study set- valued homomorphism on lattices and t-rough lattice with respect to a sublattice. this paper deals with t-rough set approach on the lattice theory. the result of this study contributes to, t-rough fuzzy set and approximation theory and proved in several papers. keywords: approximation space; lattice; prime ideal; rough ideal; t-rough set; set...

We prove that three independent fuzzy systems can uniformly approximate Bayesian posterior probability density functions by approximating the prior and likelihood probability densities as well as the hyperprior probability densities that underly the priors. This triply fuzzy function approximation extends the recent theorem for uniformly approximating the posterior density by approximating just...

Regression analysis is an area of statistics that deals with the investigation of the dependence of a variable upon one or more variables. Recently, much research has studied fuzzy estimation. There are some approaches existing in the literature for the estimation of the fuzzy regression model. Two of them are frequently used in parameter estimation, one of which is proposed by Tanaka et al [21...

The general mathematical problem of fuzzy control is an interpolation problem: a list of fuzzy input-output data, usually provided by a list of linguistic control rules, should be realized as argument-value pairs for a suitably chosen fuzzy function. However, contrary to the usual understanding of interpolation, in the actual approaches this interpolation problem is considered as a global one: ...

the main purpose of this paper is to find t-best approximations in fuzzy normed spaces. we introduce the notions of t-proximinal sets and f-approximations and prove some interesting theorems. in particular, we investigate the set of all t-best approximations to an element from a set.

In many practical applications, it is useful to represent a function f(x) by its fuzzy transform, i.e., by the “average” values Fi = ∫ f(x) ·Ai(x) dx ∫ Ai(x) dx over different elements of a fuzzy partition A1(x), . . . , An(x) (for which Ai(x) ≥ 0 and n ∑ i=1 Ai(x) = 1). It is known that when we increase the number n of the partition elements Ai(x), the resulting approximation get closer and cl...

Since almost all practical problems are fuzzy and approximate, fuzzy decision making becomes one of the most important practical approaches. However, the resulting problems are frequently complicated and difficult to solve. One effective way to overcome these difficulties is to explore the concavity or generalized concavity properties of the resulting problems. In this paper, we introduce and s...

In some cases, our uncertainty about about a quantity can be described by an interval of its possible values. If we have two or more pieces of interval information about the same quantity, then we can conclude that the actual value belongs to the intersection of these intervals. In general, we may need a fuzzy number to represent our partial knowledge. A fuzzy number can be viewed as a collecti...

Modeling and prediction in some systems requires the simultaneous approximation of mappings and their derivatives to a certain finite order. In this paper, universal approximation capabilities of fuzzy systems are extended to this situation, by showing the denseness of some general classes of fuzzy models in appropriate function spaces where distance between functions is defined in terms of the...