In this paper we address the design of a fuzzy flight controller that achieves stable and robust “aggressive” manoeuvrability for an unmanned helicopter. The fuzzy flight controller proposed consists of a combination of a fuzzy gain scheduler and linguistic (Mamdani-type) controller. The fuzzy gain scheduler is used for stable and robust altitude, roll, pitch, and yaw control. The linguistic co...

Linguistic modeling of complex irregular systems is helpful for the generation of decision making controls. In the various existing Fuzzy models, proposed by Mamdani, Sugeno, and Tsukamoto, the concepts of the set of membership functions and different Fuzzy logic rules to reason about data were addressed. The time control issues were not discussed in these models. In this paper, a new model is ...

We present a linguistic extension from a crisp model by using a codification model that allows us to implement a fuzzy system on a discrete decision model. The paper begins with an introduction to the representation of fuzzy information, followed by a discussion of the codification method and the extension of a linear associative memory to a linguistic linear associative memory. Finally, we enu...

In multiperson decision making situations, it is quite natural that different decision makers who may have different background and knowledge will provide their preferences by different kinds of preference relations. This paper proposes a linguistic multiperson decision making model (LMDMM) based on linguistic preference relations, integrating fuzzy preference relations, different types of mult...

This paper aims to extend fuzzy MULTIMOORA with linguistic reasoning and group decision-making (MULTIMOORA-FG). The new method consists of the three parts, namely the fuzzy Ratio System, the fuzzy Utopian Reference Point, and the fuzzy Full Multiplicative Form offering a robust comparison of alternatives against multiple objectives. In addition, MULTIMOORA-FG is designed to deal with triangular...

In this paper, we discuss the analysis of students’ evaluation, especially in the case of the students’ answerscripts under the evaluation grade of linguistic data. We transfer mostly linguistic data, subjective message into triangular fuzzy numbers, and use the function principle instead of the extension principle to calculate the students’ score. In addition to, we use the degree of similarit...

This paper proposes a general discussion of the handling of imprecise and uncertain information in temporal reasoning in the framework of fuzzy sets and possibility theory. The introduction of fuzzy features in temporal reasoning can be related to different issues. First, it can be motivated by the need of a gradual, linguistic-like description of temporal relations even in the face of complete...

We propose a general scheme of collective choice rule that covers a number of well-known rules. Our point of departure is, first, the set of fuzzy preference relations, and second, the linguistic aggregation rule proposed by Kacprzyk [2-4]. We reconsider this rule on a more abstract level and use the OWA operators instead of Zadeh’s fuzzy linguistic quantifiers. All collective choice rules from...

We describe the basics of fuzzy sets and fuzzy logic. Based upon the concept of linguistic values, which describe imprecise concepts using words, the basics of fuzzy rules and fuzzy inference are introduced. In the second part we briefly explain applications of fuzzy rules for function approximation using fuzzy graphs, clustering using fuzzy algorithms, and classification under uncertainty usin...

Describing and modeling a complex system is very hard and time consuming, so, we propose to use a linguistic approach introduced by Zadeh. By taking a linguistic approach we can use linguistic variables and approximate rules to characterize approximately phenomenons which are too complex or too ill-defined to be done in numerical terms. Starting from the results obtained in our previous works, ...