Applications of fuzzy sets and approximate reasoning

Schwartz, Daniel G.; Klir, George J.; Lewis, Howard B.; Ezawa, Yoshinori

doi:10.1109/5.282229

Cited by 67 publications

(23 citation statements)

References 42 publications

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“…If we have the implication p → q of two statements "p" and "q" in accordance with the present, then we can infer [11] the truth of statements based on the q which authenticity "p" and the implication p → q So we conclude the following scheme.…”

Section: Basic Rules Of Inferencementioning

confidence: 98%

Fuzzy Logic and Approximate Reasoning

Aliev¹,

Huseynov²

2014

Decision Theory With Imperfect Information

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Two of the most exemplary capabilities of the human mind are the capability of using perceptions (human knowledge) in purposeful ways and the capability of approximating perceptions by statements in natural language. Understanding these capabilities and emulating them by linguistic approximation is the crux of our thesis. There has been a rapid growth in the number and variety of applications of fuzzy logic. In a narrow sense, fuzzy logic is a logical system which is an extension of multivalued logic and is intended to serve as logic of approximate reasoning. But in a wider sense, fuzzy logic is more or less synonymous with the theory of fuzzy sets. In classical logic the propositional value of a statement is either true (1) or false (0) but in lukasiewicz logic we gave value as a truthfulness to a certain proposition between [0, 1]. As a generalization of many valued logic, fuzzy logic was established in order to deal with those fuzzy propositions and to underlie approximate reasoning. We have calculated the fuzzy truth values and compare the results of different operations (conjunction, disjunction etc) with the approach to Baldwin's (1979) and with the help of modus ponens law (If p → q and p then q .).There are many chemical reactions that are very sensitive and a little change in temperature and particle size can create serious problems. We have developed the idea of approximate reasoning and fuzzy logic to find the approximate value of reaction rate with the given conditions by means of the extended modus ponens law. The methodology is very simple and can be applied to several other chemical reactions in the similar way by connecting AND and OR operations. The result Q can be found by the fuzzy relation equation Q = P o R where "o" is the max-min composition of P and R operation. Result Q for the certain situation is in the form of fuzzy set, in which we choose the value with maximum membership degree.iv

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Section: Basic Rules Of Inferencementioning

confidence: 98%

Fuzzy Logic and Approximate Reasoning

Aliev¹,

Huseynov²

2014

Decision Theory With Imperfect Information

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“…(18). However, the final coefficients of a PID controller are not equal to these rules, but it is a good initial point for tuning the parameters.…”

Section: Pid Controllermentioning

confidence: 99%

“…Due to imperfections of PID controllers, the possibility of replacing a PID controller with the FLC is proposed [18]. Since human knowledge is used for designing fuzzy controllers, there are many ways to design FLCs.…”

Section: Fuzzy Pi+d Controllermentioning

confidence: 99%

“…Among these methods, a fuzzy logic controller (FLC) can be designed based on human knowledge when system mathematical models are unknown or complicated because of nonlinear characteristics and uncertainties, and a suitable FLC can overcome environmental variations during operation [18]. Thus, in the past 3 decades, FLCs have replaced conventional controllers in many applications and industries.…”

Section: Introductionmentioning

confidence: 99%

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A comparison of fuzzy logic and PID controllers to control transmitted power using a TCSC

Soreshjani¹,

Abjadi²,

Kargar³

et al. 2014

Turk J Elec Eng & Comp Sci

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Nowadays, the use of flexible AC transmission systems (FACTS) is an economical and interesting approach to improve power transfer capability. The thyristor-controlled series capacitor, as a member of the FACTS family, can control interrelated parameters with dynamism due to its ability of rapid control and stabilization. Regardless of all of the works in this area, the control of transmitted power through the design of the firing angle controller is still missing. In this paper, first, the open-loop firing angle controller and its sensitivities are analyzed to fill in this gap. Next, closed-loop controllers such as PID and fuzzy controllers are designed and simulated in MATLAB/Simulink software. Simulation results show that the fuzzy logic controller has a better response, although it is designed with minimum, simple, triangle membership functions and reduced rule bases.

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“…Since the late 1980s, control has become the area to which fuzzy systems are most widely applied today. This wide and diverse range of successful applications of fuzzy technologies has been responsible for the increasing interest in the subject area [2]. In the 1090s, fuzzy logic issues have been introduced to the electrical engineering curriculum in tertiary institutions [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Design of a fuzzy controller: some experience

Negnevitsky

10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297)

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Abstract-This paper describes the design and implementation of the fuzzy controller for an overhead crane model. A model used in this project was a laboratory model of the gantry cranes commonly seen in dockyards and factories. The fuzzy controller is used for suppressing load swing while positioning the trolley of an overhead crane. Simulation and experimental results are included to verify the validity of the controller developed. Further discussions on the utilisation of this laboratory model is provided.

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Applications of fuzzy sets and approximate reasoning

Cited by 67 publications

References 42 publications

Fuzzy Logic and Approximate Reasoning

Fuzzy Logic and Approximate Reasoning

A comparison of fuzzy logic and PID controllers to control transmitted power using a TCSC

Design of a fuzzy controller: some experience

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