We contrast the concept underlying t-norm-based propositional fuzzy logics with the problem to whose solution fuzzy logics are frequently suggested as helpful – namely, to find a model of reasoning with vague information. We argue that fuzzy logics are useful as long as truth values can be identified with the meaning of the considered propositions. This, however, is rarely the case in practice;...

In order to approximate any nonlinear system, not just affine nonlinear systems, generalized T-S fuzzy systems, where the control variables and the state variables, are all premise variables are introduced in the paper. Firstly, fuzzy spaces and rules were determined by using ant colony algorithm. Secondly, the state-space model parameters are identified by using genetic algorithm. The simulati...

Fuzzy sets as proposed by Zadeh (1965) are a generalization of classical set theory, in which objects, instead of just being members of a set or not, have a gradual degree of membership. Fuzzy rule-based systems (FRBS) have been used in the past successfully in many applications. They are competitive methods for classification and regression, especially for complex problems. One of their leadin...

This paper deals with bimatrix games in uncertainty environment based on several types of ordering, which Maeda proposed. But Maeda’s models was just made based on symmetrical triangle fuzzy variable. In this paper, we generalized Maeda’s model to the non-symmetrical environment. In other words, we investigated the fuzzy bimatrix games based on nonsymmetrical L-R fuzzy variables. Then the pseud...

This paper extends the traditional Fuzzy C-Means clustering method to a generalized fuzzy clustering model. According to most applications, this fuzzy clustering model briefly includes 3 parts: feature extractor transfers original objects information to desired feature data; fuzzy cluster analyzer gets cluster information from the feature data; and post treatment obtains the final results based...

Just like rough set theory, fuzzy set theory addresses the topic of dealing with imperfect knowledge. Recent investigations have shown how both theories can be combined into a more flexible, more expressive framework for modelling and processing incomplete information in information systems. At the same time, intuitionistic fuzzy sets have been proposed as an attractive extension of fuzzy sets,...

In this paper, Swing-up and Stabilization of the Rotary inverted pendulum (RIP) is done through the fuzzy controller.The attraction of this paper is achieving the above stated aim through lesser number of rules. RIP is highly unstable and nonlinear in nature, so stabilization of the RIP is itself a challenging task. Swing-up mechanism in RIP is a type of unstable mechanism which is done effecti...

Abstract This chapter offers examples illustrating how the ‘Solver’ feature of Excel can be used to solve simultaneous equations and unconstrained constrained optimization models. other features any or simulation models introduced in this book.