It is well-known that the choice of membership functions is a key problem in the design of a fuzzy controller. The aim of this paper is thus to give a further contribution in this direction. In particular, the performance of the Mamdani-type fuzzy controller with piece wise linear membership functions is discussed in details, taking into account features such as overlapping, completeness level,...

Abstract This article presents a development of a fuzzy based nominal characteristic trajectory following (NCTF) controller for continuous motion control. A new structure is proposed in order to achieve excellent performance of tracking to a continuous reference input and also for point-to-point positioning task. The proposed structure maintains the NCTF controller simple configuration which is...

In this paper, we study a pair of fuzzy primal–dual linear programming problems and calculate duality results using an aspiration level approach. We use an exponential membership function, which is in contrast to the earlier works that relied on a linear membership function. As the fuzzy environment causes a duality gap, we investigate how choosing the exponential membership function impacts th...

This paper proposes to analyze two flow line systems in which we include possibilistic data -the priority-discipline is possibilistic instead of probabilisticand measure the performances of the systems with the effectiveness measure “waiting time in queue”. In a previous work we have analyzed and developed a queuing model with uncertain priority-discipline, using Zadeh’s extension principle. Be...

By adding the complement operator (¬), extended regular expressions (ERE ) can encode regular languages non-elementarily more succinctly than regular expressions. The ERE membership problem asks whether a word w of size n belongs to the language of an ERE R of size m. Unfortunately, the best known membership algorithms are either non-elementary in m or otherwise require space Ω(n) and time Ω(n)...

In this paper, application of possibilistic clustering techniques to identification of local linear models will be discussed. In particular, a generalisation of some possibilistic algorithms in the bibliography is obtained. With the presented procedures, a trade-off between an “expected shape” of the membership functions and model fit can be stated. Possibilistic clustering may allow for better...

Corresponding Author: Andréia Alves dos Santos Schwaab Department of Informatics and Statistics, Federal University of Santa Catarina, Florianopolis, Brazil Email:[email protected] Abstract: Generation of membership functions is an important step in construction of fuzzy systems. Since membership functions reflect what is known about the variables involved in a problem, when they are c...

Functionality-based recognition systems recognize objects at the category level by reasoning about how well the objects support the expected function. Such systems naturally associate a \measure of goodness" or \membership value" with a recognized object. This measure of goodness is the result of combining individual measures, or membership values, from potentially many primitive evaluations of...

In this paper, we incorporate the concept of fuzzy set theory into the support vector regression (SVR). In our proposed method, target outputs of training samples are considered to be fuzzy numbers and then, membership function of actual output (objective hyperplane in high dimensional feature space) is obtained. Two main properties of our proposed method are: (1) membership function of actual ...

Rubin and Narsimhan [1984] proposed a method for formulating fuzzy priorities in goal programming. They used the concept that the membership function based on nested priorities has to be concave to solve the fuzzy goal programming problem by linear programming method. In this paper, we relax the condition of concave membership function by quasi concave membership function. We showed that the fu...