engleski

Fuzzy Logic - Applications, Systems and Technologies

In the second half of the past century, the fuzzy theory for solving engineering problems with uncertainties has grown enormously. The ability to perform control tasks in unknown environments is one of the most important characteristics of any intelligent control system. In addition, fuzzy logic provides an inference structure that enables the human reasoning capabilities to be applied to artificial knowledge-based systems. This book presents a few examples of fuzzy logic applications in electrical, chemical, computer and textile engineering with a simple and readable approach. The book is divided into five chapters. Chapter 1 presents adaptive neuro-fuzzy interface system to predict the pain using the visual scale on patients. The American Hospira company has developed a patient-controlled analgesic device which uses the neuro-fuzzy system to determine the timing of the anesthetic by patient’s own discretion and without the need for the medical staff. In Chapter 2, the authors present application of fuzzy logic techniques to two types of environmental systems. The first type deals with the supervision, diagnosis of acidification states and control of waste treatment plants. Application of fuzzy logic techniques are presented and discussed. In the second type, fuzzy logic techniques are applied to the integration of environmental criteria. The selection of the best packaging materials for a beverage bottle and selection of the best model of children’s footwear where used to illustrate this type of the environmental system. In Chapter 3, two optimization methods have been proposed and applied to solve practical problems related to electric power system operation and control. The first method proposes an adaptation of the gravitational search algorithm to improve the solution of dynamic economic dispatch considering practical generator constraints. The second proposed method based on the particle swarm optimization is proposed for solving multi objective optimal power flow considering distributed shunt STATCOMs. The robustness of the proposed strategy was tested on many standard electrical networks. In Chapter 4, the authors present the fuzzy logic approach in color matching processes on surface – structural characteristics of textile samples. The main idea was to examine the approach using fuzzy logic based technique in order to provide the method that would include surface parameters of textile samples that are of importance in color applying on structured textile surfaces. It was confirmed that the fuzzy logic reasoning would have its application in control of surface structure influence of colored textiles, especially for lighter shades. Finally, Chapter 5 presents a few examples of chemical implementation of fuzzy logic operators. Both chromogenic spiro-oxazine and oscillating Belousov-Zhabotinsky reactions allow the fundamental fuzzy logic operators to be implemented. The fuzzy logic systems based on the oscillating Belousov-Zhabotinsky reaction have the advantage of a faster reset time. The fuzzy logic systems based on the chromogenism of spiro-oxazine reaction are particularly appealing because they are based on a defuzzification procedure imitating the way humans distinguish colours.

Fuzzy Logic; Fuzzy Neural Networks; Environmental Systems; FACTS; Color Matching; Molecules

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