• Title/Summary/Keyword: Fuzzy Reasoning Method

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Intelligent Control of Mobile robot Using Fuzzy Neural Network Control Method (퍼지-신경망 제어기법을 이용한 Mobile Robot의 지능제어)

  • 정동연;김용태;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.10a
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    • pp.235-240
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    • 2002
  • This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

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An Intelligent Control of TRack Vehicle Using Fuzzy-Neural Network Control Method (퍼지-신경회로망 제어기법에 의한 궤도차량의 지능제어)

  • 신행봉;김용태;조길수;한성현
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1999.05a
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    • pp.210-215
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    • 1999
  • In this paper, a new approach to the dynamic control technique for track vehicle system using fuzzy-neural network control technique is proposed. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.

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FUZZY CONTROL LAW OF HIGHLY MANEUVERABLE HIGH PERFORMANCE AIRCRAFT

  • Sul Cho;Park, Rai-Woong;Nam, Sae-Kyu;Lee, Man-Hyung
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.205-209
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    • 1998
  • A synthesis of fuzzy variable structure control is proposed to design a high-angle-of-attack flight system for a modification version of the F-18 aircraft. The knowledge of the proportional, integral, and derivative control is combined into the fuzzy control that addresses both the highly nonlinear aerodynamic characteristics of elevators and the control limit of thrust vectoring nozzles. A simple gain scheduling method with multi-layered fuzzy rules is adopted to obtain an appropriate blend of elevator and thrust vectoring commands in the wide operating range. Improving the computational efficiency, an accelerated kernel for on-line fuzzy reasoning is also proposed. The resulting control system achieves the good flying quantities during a high-angle-of- attack excursion. Thus the fuzzy logic can afford the control engineer a flexible means of deriving effective control laws in the nonlinear flight regime.

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A Study on the Dosage ate Control of the Pre-Chorine in Water Purification using Fuzzy Inference Technique (퍼지 론기법 정수공정의 전염소주입율 제어에 관한 연구)

  • 이상석;소명옥;이준탁
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.2 no.1
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    • pp.89-95
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    • 1996
  • This paper describes a fuzzy controlled pre-chlorination technique for purifying the pulluted raw water in water purification lants. For the purpose of obtaining the high quality water, the appropriate pre-chlorine dosage rate has to be continuously adjusted according to a change in quality of a intake raw water, weather, solar nergy mount, temperature and etc. Therefore, the method of expressing an expert's empirical knowledge cumulated from his past carrier by fuzzy reasoning and the fuzzy controller design technique is necessary.In this paper fuzzy membership functions and rules accordingto emprircal knowledge and experimental field data were obtained, And also fuzzy cintriller design using four feedforward components for the determination of pre-chlorine dosage rate and four feedback ones for the compensation of its dosage rate with residual chlorine and its change rate, was executed.

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EXPERT SYSTEM FOR A NUCLEAR POWER PLANT ACCIDENT DIAGNOSIS USING A FUZZY INFERENCE METHOD

  • Lee, Mal-Rey;Oh, Jong-Chul
    • Journal of applied mathematics & informatics
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    • v.8 no.2
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    • pp.505-518
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    • 2001
  • The huge and complicated plants such as nuclear power stations are likely to cause the operators to make mistakes due to a variety of inexplicable reasons and symptoms in case of emergency. That’s why the prevention system assisting the operators is being developed for. First of all. I suggest an improved fuzzy diagnosis. Secondly, I want to demonstrate that a classification system of nuclear plant’s accident investigating the causes of accidents foresees possible problems, and maintains the reliability of the diagnostic reports in spite of improper working in part. In the event of emergency in a nuclear plant, a lot of operational steps enable the operators to find out what caused the problems based on an emergent operating plan. Our system is able to classify their types within twenty to thirty seconds. As so, we expect the system to put down the accidents right after the rapid detection of the damage control-method concerned.

Local Binary Feature and Adaptive Neuro-Fuzzy based Defect Detection in Solar Wafer Surface (지역적 이진 특징과 적응 뉴로-퍼지 기반의 솔라 웨이퍼 표면 불량 검출)

  • Ko, JinSeok;Rheem, JaeYeol
    • Journal of the Semiconductor & Display Technology
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    • v.12 no.2
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    • pp.57-61
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    • 2013
  • This paper presents adaptive neuro-fuzzy inference based defect detection method for various defect types, such as micro-crack, fingerprint and contamination, in heterogeneously textured surface of polycrystalline solar wafers. Polycrystalline solar wafer consists of various crystals so the surface of solar wafer shows heterogeneously textures. Because of this property the visual inspection of defects is very difficult. In the proposed method, we use local binary feature and fuzzy reasoning for defect detection. Experimental results show that our proposed method achieves a detection rate of 80%~100%, a missing rate of 0%~20% and an over detection (overkill) rate of 9%~21%.

A Novel Speed Estimation Method of Induction Motors Using Real-Time Adaptive Extended Kalman Filter

  • Zhang, Yanqing;Yin, Zhonggang;Li, Guoyin;Liu, Jing;Tong, Xiangqian
    • Journal of Electrical Engineering and Technology
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    • v.13 no.1
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    • pp.287-297
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    • 2018
  • To improve the performance of sensorless induction motor (IM) drives, a novel speed estimation method based on the real-time adaptive extended Kalman filter (RAEKF) is proposed in this paper. In this algorithm, the fuzzy factor is introduced to tune the measurement covariance matrix online by the degree of mismatch between the actual innovation and the theoretical. Simultaneously, the fuzzy factor can be continuously self-tuned tuned by the fuzzy logic reasoning system based on Takagi-Sugeno (T-S) model. Therefore, the proposed method improves the model adaptability to the actual systems and the environmental variations, and reduces the speed estimation error. Furthermore, a simple exponential function based on the fuzzy theory is used to reduce the computational burden, and the real-time performance of the system is improved. The correctness and the effectiveness of the proposed method are verified by the simulation and experimental results.

Development of Traffic Conflict Technique with Fuzzy Reasoning Theory (퍼지추론을 적용한 교통상충기법(TCT) 개발)

  • ;;;今田寬典
    • Journal of Korean Society of Transportation
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    • v.20 no.1
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    • pp.55-63
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    • 2002
  • It has been known well that Traffic Conflict Technique(TCT) used to evaluate the safety of intersections in the case of shortage of traffic accidents data and surveying time. Because data for using in traffic conflict technique that is collected by trained surveyors, it is rely on the knowledge, experience and the characteristics of them. The data of surveying generate varying result. So, its variance must minimize and then it is considered of calculating in traffic conflict technique however obviously technique to minimize has not developed until now. So, this paper has a focus on the technical method to minimize the variance. For this, it applied the fuzzy reasoning theory to the existed traffic conflict technique that is the most comprehensive method in the country and then developed the new traffic conflict technique model. Fuzzy reasoning theory is a very appropriate method for minimizing the variance among surveyors because it can systematically calculate the uncertainty of surveyors by approximation reasoning structure. The result of analysis from pilot study, the new Procedure in this Paper minimized the variance by 53 Percentiles and it increased the value of conversion factor two times than the exited traffic conflict technique. The method proposed in this paper, it can be used for evaluating the safety of intersection, and before and after analysis of improving Project of black spots.

A Study on the multcriteria Fuzzy Fire Detector (계층적 Fuzzy 감지기에 대한 연구)

  • 서영수;백동현
    • Fire Science and Engineering
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    • v.11 no.2
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    • pp.45-53
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    • 1997
  • In this article, the Fuzzy Logic as the principle of the multcriteria fire detector is used to determine whether the fire takes out or not. The main contents of this method as follow; most of all, the degree of the fire is represented as the type of the Fuzzy, and then it is possible to examine whether the fire takes out or not by the principle of the Fuzzy Logic. The input fators of the Fuzzy fire detector are temperature sensor, smoke sensor, light sensor applied to digital type. On the result of this study, the first, the number of the case of the nonfire alarm which is represented in the existing fire detector is reduced, and the second, the applicability of the fuzzy detector is demonstrated by the test.

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Discretization of Numerical Attributes and Approximate Reasoning by using Rough Membership Function) (러프 소속 함수를 이용한 수치 속성의 이산화와 근사 추론)

  • Kwon, Eun-Ah;Kim, Hong-Gi
    • Journal of KIISE:Databases
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    • v.28 no.4
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    • pp.545-557
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    • 2001
  • In this paper we propose a hierarchical classification algorithm based on rough membership function which can reason a new object approximately. We use the fuzzy reasoning method that substitutes fuzzy membership value for linguistic uncertainty and reason approximately based on the composition of membership values of conditional sttributes Here we use the rough membership function instead of the fuzzy membership function It can reduce the process that the fuzzy algorithm using fuzzy membership function produces fuzzy rules In addition, we transform the information system to the understandable minimal decision information system In order to do we, study the discretization of continuous valued attributes and propose the discretization algorithm based on the rough membership function and the entropy of the information theory The test shows a good partition that produce the smaller decision system We experimented the IRIS data etc. using our proposed algorithm The experimental results with IRIS data shows 96%~98% rate of classification.

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