This paper suggests a new stability analysis theorem dedicated to a class of fuzzy logic control systems. The fuzzy logic control systems consist of nonlinear Single Input-Single Output (SISO) discrete-time processes controlled by Takagi-Sugeno fuzzy logic controllers. The stability analysis is conducted on the basis of Lyapunov’s direct method with quadratic Lyapunov function candidates. The t...

Congestion is the problem that occurs due to saturation of network resources. Despite the implementation of traditional congestion control algorithms such as Transmission Control Protocol (TCP/IP), congestion remains a critical issue in computer and ATM networks. Fuzzy Logic is applied to solve the congestion control problem as communication networks are difficult to model using traditional con...

Fuzzy logic has been successfully deployed in many realworld automatic control systems including subway systems, autofocus cameras, washing machines, automobile transmissions, air-conditioners, industrial robots, aerospace, and autonomous robot navigation. In contrast, the use of fuzzy logic in telecommunication systems and networks is recent and limited. Fundamentally, Zadeh’s fuzzy set theory...

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Fuzzy logic has become an important tool for number of different applications ranging from the control of engineering system to artificial intelligence. Practical applications of fuzzy logic pose a unique set of problems. The design of systems, which apply fuzzy logic to make use of human knowledge and experience, is a daunting task without facing engineering problems of real world systems. In ...

New trends and the effect of key factors influence the quality of the holes produced by ECM processes. Researchers developed a fuzzy logic controller by adding intelligence to the ECM process. Maintaining optimum ECM process conditions ensures higher machining efficiency and performance. This paper presents the development of a fuzzy logic controller to add intelligence to the ECM process. An e...

This paper presents the development of a fuzzy logic library using the dynamic simulation software SIMULINK under MATLAB environment. The developed library includes the main blocks: MIN (minimum operation), MAX (maximum operation), MFG (membership function generator), FUZ (fuzzifier to convert a crisp input into a fuzzy labels), F-RULES (fuzzy rules matrix), F-INF (Min-Max fuzzy inference), DEF...

This research suggests a new type of inte1,ligent system based on new approaches to generation and selection of family of fuzzy logics. It is based on new generalizedl strategy of designing of fuzzy intelligent systems. Family of fuzzy logics can be generated by T-norms axiomatic system to choose the logic, that is the most suitable to expert way of thinking. Then the selected fuzzy logic is te...

This paper is a contribution to the development of model theory of fuzzy logic in narrow sense. It is known that there are many formal systems of fuzzy logic, most of them having traditional syntax and many-valued semantics. Our logic is further generalization, where also syntax is evaluated, i.e. we may consider fuzzy sets of axioms. In the paper we show the possibilities how to construct the ...

In this paper we developed a Type-2 Fuzzy Logic System (T2FLS) in order to model a batch biotechnological process. Type-2 fuzzy logic systems are suitable to drive uncertainty like that arising from process measurements. The developed model is contrasted with an usual type-1 fuzzy model driven by the same uncertain data. Model development is conducted, mainly, by experimental data which is comp...