The way engineers use fuzzy control in real world applications is often not coherent with an understanding of the control rules as logical statements or implications. In most cases fuzzy control can be seen as an interpolation of a partially speciied control function in a vague environment, which reeects the indistinguishability of measurements or control values. In this paper we show that equa...

The situation and trends in the application of fuzzy logic to control multi-input/multi-output (MIMO) systems are analyzed. The basic steps in designing a control system are considered. Fuzzy control applications are either knowledge-based or model-based. In model-based approaches, the first step is process modeling: Usually, interpolation and universal approximation are the two main features t...

Fuzzy systems working with a sparse rule base apply special reasoning techniques in order to ensure the acceptable output in case of observations hitting the gap between the antecedent parts of the rules, too. The methods that follow the generalized methodology of the fuzzy rule interpolation (GM) [1] produce the conclusion in two steps. First a new rule is interpolated in the position determin...

This paper introduces a definition of influence zones for fuzzy sets. The notion of fuzzy skeleton by influence zones (SKIZ), or fuzzy generalized Voronoï diagram, is derived. These definitions are based on fuzzy dilations and their interpretations in terms of distances. As another contribution, we show how this notion can be used to define a fuzzy median set, and a series of fuzzy sets interpo...

Functional laws may be known only at a finite number of points, and then the function can be completed by interpolation techniques obeying some smoothness conditions. We rather propose here to specify constraints by means of gradual rules for delimiting areas where the function may lie between known points. Such an approach results in an imprecise interpolation graph whose shape is controlled b...

Video signals can be interlaced or noninterlaced. The interlaced scan format suffers from several possible artifacts such as flicker, twitter, and crawling. De-interlacing algorithms convert an interlaced video signal to the progressive scan format by interpolating the missing lines. These algorithms can be used to improve picture quality, but can also be necessary to use interlaced video on pr...

This paper presents an approach for stabilization of equilibria in recurrent fuzzy systems. This type of dynamic fuzzy systems being defined via linguistic rules can be interpreted as interpolation between constant gradients, and therefore as hybrid dynamical system. It is shown that the latter viewpoint allows for a precise description of the system dynamics, but on the other hand lacks transp...

We present a fuzzy decision support system that can be used in traffic control centers to provide a limited list of appropriate combinations of traffic control measures for a given traffic situation. The system is part of a larger traffic decision support system (TDSS) that can assist the operators of traffic control centers when they have to reduce non-recurrent congestion using a network-wide...

Fuzzy arithmetic provides a powerful tool to introduce uncertainty into mathematical models. With Zadeh’s extension principle, one can obtain a fuzzy extension of any objective function. Computing expensive multivariate functions of fuzzy numbers, however, often poses a difficult problem due to non-applicability of common fuzzy arithmetic algorithms, severe overestimation, or very high computat...

The aim of this paper is to propose a criterion to estimate the design, from experimental data, of a fuzzy inference system, when data are sparse. This lack of data is important and may improve the generalisation ability of fuzzy systems (0). Several methods have been proposed to obtain automatic fuzzy rules from sparse training data. In (0), the authors first construct fuzzy rules from collect...