Faculty of Technology Department of Informatics by Majid Almaraashi This thesis reports the work of using simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of type-1 and type-2 fuzzy logic systems to maximise their modelling ability. There...

Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an adaptive control scheme for a class of nonlinear systems. Firstly, the fuzzy T-S model is used to approximate the nonlinear systems, and the fuzzy control law of the fuzzy model is derived by the linear matrix inequality. Secondly, the adaptive fuzzy logic systems are con...

In the past year I have been inundated with articles on fuzzy logic as well as encouraged to use it for control systems. After reading some articles on fuzzy logic control, listening to a seminar by Zadeh, and attending a one day course on Intelligent Control, I started forming an opinion about how fuzzy logic control works. I believe that there are some fundamental pieces of information not pr...

Fuzzy logic programs are a useful framework for handling uncertainty in logic programming; nevertheless, there is the need for modelling adaptation of fuzzy logic programs. In this paper, we first overview weighted fuzzy programs, which bring fuzzy logic programs and connectionist models closer together by associating significance weights with the atoms of a logic rule: by exploiting the existe...

‘‘Is there a need for fuzzy logic?” is an issue which is associated with a long history of spirited discussions and debate. There are many misconceptions about fuzzy logic. Fuzzy logic is not fuzzy. Basically, fuzzy logic is a precise logic of imprecision and approximate reasoning. More specifically, fuzzy logic may be viewed as an attempt at formalization/mechanization of two remarkable human ...

We present a novel approach to fuzzy description logic programs (or simply fuzzy dl-programs) under the answer set semantics, which is a tight integration of fuzzy disjunctive logic programs under the answer set semantics with fuzzy description logics. From a different perspective, it is a generalization of tightly coupled disjunctive dl-programs by fuzzy vagueness in both the description logic...

This paper proposes an optimal design for interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic system. In this method, the fuzzy c-means clustering algorithm is used to determine structure of fuzzy rule as well as number of rules. A hybrid between chaos firefly algorithm and genetic algorithms (CFGA) is developed, which is used to find the desirable parameters of membership functions and conseq...

Fuzzy logic is an extension of the classical (Boolean) logic that can be used to handle mathematically the vagueness of human linguistics and thinking (Tanaka, 1996). In other words, it provides a logical system to formalize approximate reasoning (Zedeh, 1994; 1996). Actually, the foundation of fuzzy logic is the fuzzy set theory that was initially introduced by Zedeh (1965). However, currently...

The application of fuzzy-logic method in control of systems has recently attracted increasing interest. Fuzzy controllers exhibit a simple and robust framework for specifying control laws that accommodate uncertainty and imprecision. This paper reviews fuzzy-logic applications for robot systems. An introduction to fuzzy logic method is presented, then a short literature review is provided and t...