• Title/Summary/Keyword: Fuzzy Application

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Application of Fuzzy Algorithm with Learning Function to Nuclear Power Plant Steam Generator Level Control

  • Park, Gee-Yong-;Seong, Poong-Hyun;Lee, Jae-Young-
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1054-1057
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    • 1993
  • A direct method of fuzzy inference and a fuzzy algorithm with learning function are applied to the steam generator level control of nuclear power plant. The fuzzy controller by use of direct inference can control the steam generator in the entire range of power level. There is a little long response time of fuzzy direct inference controller at low power level. The rule base of fuzzy controller with learning function is divided into two parts. One part of the rule base is provided to level control of steam generator at low power level (0%∼30% of full power). Response time of steam generator level control at low power level with this rule base is shown generator level control at low power level with this rule base is shown to be shorter than that of fuzzy controller with direct inference.

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A Fuzzy Spatiotemporal Data Model and Dynamic Query Operations

  • Nhan, Vu Thi Hong;Kim, Sang-Ho;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.564-566
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    • 2003
  • There are no immutable phenomena in reality. A lot of applications are dealing with data characterized by spatial and temporal and/or uncertain features. Currently, there has no any data model accommodating enough those three elements of spatial objects to directly use in application systems. For such reasons, we introduce a fuzzy spatio -temporal data model (FSTDM) and a method of integrating temporal and fuzzy spatial operators in a unified manner to create fuzzy spatio -temporal (FST) operators. With these operators, complex query expression will become concise. Our research is feasible to apply to the management systems and query processor of natural resource data, weather information, graphic information, and so on.

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Fuzzy Preference Based Interactive Fuzzy Physical Programming and Its Application in Multi-objective Optimization

  • Zhang Xu;Huang Hong-Zhong;Yu Lanfeng
    • Journal of Mechanical Science and Technology
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    • v.20 no.6
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    • pp.731-737
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    • 2006
  • Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer.

A Computer Oriented Solution for the Fractional Boundary Value Problem with Fuzzy Parameters with Application to Singular Perturbed Problems

  • Asklany, Somia A.;Youssef, I.K.
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.223-227
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    • 2021
  • A treatment based on the algebraic operations on fuzzy numbers is used to replace the fuzzy problem into an equivalent crisp one. The finite difference technique is used to replace the continuous boundary value problem (BVP) of arbitrary order 1<α≤2, with fuzzy boundary parameters into an equivalent crisp (algebraic or differential) system. Three numerical examples with different behaviors are considered to illustrate the treatment of the singular perturbed case with different fractional orders of the BVP (α=1.8, α=1.9) as well as the classical second order (α=2). The calculated fuzzy solutions are compared with the crisp solutions of the singular perturbed BVP using triangular membership function (r-cut representation in parametric form) for different values of the singular perturbed parameter (ε=0.8, ε=0.9, ε=1.0). Results are illustrated graphically for the different values of the included parameters.

COMPLETELY V-REGULAR ALGEBRA ON SEMIRING AND ITS APPLICATION IN EDGE DETECTION

  • G.E. CHATZARAKIS;S. DICKSON;S. PADMASEKARAN;J. RAVI
    • Journal of applied mathematics & informatics
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    • v.41 no.3
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    • pp.633-645
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    • 2023
  • In this paper, Completely V-Regular on semiring is defined and used to derive new theorems with some of its properties. This paper also illustrates V-Regular algebra and Completely V-Regular Algebra with examples and properties. By extending completely V-Regular to fuzzy, a new concept, fuzzy V-Regular is brought out and fuzzy completely V-Regular algebra is introduced too. It is also developed by defining the ideals of Completely V -Regular Algebra and fuzzy completely V-Regular algebra. Finally, this fuzzy algebra concept is applied in image processing to detect edges. This V-Regular Algebra is novel in the research area.

Color Seal Extraction of Document Images using An Extended Fuzzy Integral (확장된 퍼지적분을 이용한 문서영상의 컬러낙관 추출)

  • Park, In-Kyu;Choi, Gyoo-Seok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.1
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    • pp.31-37
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    • 2009
  • This paper casts an application of an extended fuzzy integral on the selective extraction of color clusters characterized by a particular color hue from color document images. Despite of the negative role of fuzzy integral, the presented approach attains the detection of the seals through the neighborhood information via the center of area method. The conventional fuzzy integral evaluates the negative aspects of the importance about the items by min operator, which result in the discontinuous parts of seals. In an attempt to cope with the drawback our approach considers the integral aspects via the center of area method, which results in the robustness of the images. Finally, the framework is successfully tested on a data set formed by documents from a real application for the detection.

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Application of the Fuzzy Method to Improve GIS Geomorphological Method of Predicting Flood Vulnerable Area

  • Kim Su Jeong;Yom Jae-Hong;Lee Dong-Cheon
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.264-267
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    • 2004
  • In identifying flood vulnerable areas, three methods are generally deployed: the geomorphology method which is based on topographic features; the past evidence method based on observed data of past actual floods; and, prediction of flood areas through hydrologic models. This study aims to improve the prediction model of the geomorphology method through the application of fuzzy method in GIS modeling. The generally used GIS method of superimposing thematic map layers assumes crisp boundaries of the layers, which results in either risk-averse solutions or risk-taking solutions. The introduction of fuzzy concepts to processing of evaluation criteria (DEM, slope, aspect) solves this problem. As the result of applying the fuzzy method to a test site in the west Nak-Dong river, similar flood vulnerable areas were predicted as when using the conventional Boolean criteria. The resulting map, however, showed varying degree of uncertainty of flooding in these areas. This extra information is deemed to be valuable in taking phased actions during flood response, leading to a more effective and timely decision-making.

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Modeling and Control of Intersection Network using Real-Time Fuzzy Temporal Logic Framework (실시간 퍼지 시간논리구조를 이용한 교차로 네트워크의 모델링과 제어)

  • Kim, Jung-Chul;Lee, Won-Hyok;Kim, Jin-Kwon
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.4
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    • pp.352-357
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    • 2007
  • This paper deals with modeling method and application of Fuzzy Discrete Event System(FDES). FDES have characteristics which Crisp Discrete Event System(CDES) can't deals with and is constituted with the events that is determined by vague and uncertain judgement like biomedical or traffic control. We proposed Real-time Fuzzy Temporal Logic Framework(RFTLF) to model Fuzzy Discrete Event System. It combines Temporal Logic Framework with Fuzzy Theory. We represented the model of traffic signal systems for intersection to have the property of Fuzzy Discrete Event System with Real-time Fuzzy Temporal Logic Framework and designed a traffic signal controller for smooth traffic flow. Moreover, we proposed the method to find the minimum-time route to reach the desired destination with information obtained in each intersection. In order to evaluate the performance of Real-time Fuzzy Temporal Logic Framework model proposed in this paper, we simulated unit-time extension traffic signal controller model of the latest signal control method on the same condition.

Fuzzy PID Control by Grouping of Membership Functions of Fuzzy Antecedent Variables with Neutrosophic Set Approach and 3-D Position Tracking Control of a Robot Manipulator

  • Can, Mehmet Serhat;Ozguven, Omerul Faruk
    • Journal of Electrical Engineering and Technology
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    • v.13 no.2
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    • pp.969-980
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    • 2018
  • This paper aims to design of the neutrosophic fuzzy-PID controller and it has been compared with the conventional fuzzy-PID controller for position tracking control in terms of robustness. In the neutrosophic fuzzy-PID controller, error (e) and change of error (ce) were assessed separately on two fuzzy inference systems (FISs). In this study, the designed method is different from the conventional fuzzy logic controller design, membership degrees of antecedent variables were determined by using the T(true), I(indeterminacy), and F(false) membership functions. These membership functions are grouped on the universe of discourse with the neutrosophic set approach. These methods were tested on three-dimensional (3-D) position-tracking control application of a spherical robot manipulator in the MATLAB Simulink. In all tests, reference trajectory was defined for movements of all axes of the robot manipulator. According to the results of the study, when the moment of inertia of the rotor is changed, less overshoot ratio and less oscillation are obtained in the neutrosophic fuzzy-PID controller. Thus, our suggested method is seen to be more robust than the fuzzy-PID controllers.

2-Layer Fuzzy Controller for Behavior Control of Mobile Robot (이동로봇의 행동제어를 위한 2-Layer Fuzzy Controller)

  • Sim, Kwee-Bo;Byun, Kwang-Sub;Park, Chang-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.3
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    • pp.287-292
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    • 2003
  • The ability of robot is being various and complex. The robot is utilizing distance, image data and voice data for sensing its circumstance. This paper suggests the 2-layer fuzzy control as the algorithm that control robot with various sensor information. In a obstacle avoidance, it utilizes many range finders and classifies them into 3parts(front, left, right). In 3 sub-controllers, the controller executes fuzzy conference. And then it executes combined control with a combination of outputs of 3 sub-controllers in the second step. The text compares the 2-layer fuzzy controller with the hierarchical fuzzy controller that has analogous structure. And the performance of the 2-layer fuzzy controller is confirmed by application this controller to robot following, simulation to each other and real experiment.