• Title/Summary/Keyword: Fuzzy sensor algorithm

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Enhanced Auto-focus algorithm detecting target object with multi-window and fuzzy reasoning for the mobile phone (목적물 인식 및 자동 선택이 가능한 모바일 폰 용 자동초점 알고리즘)

  • Lee, Sang-Yong;Oh, Seung-Hoon;Kim, Soo-Won
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.44 no.3 s.357
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    • pp.12-19
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    • 2007
  • This paper proposes the enhanced auto-focus algorithm detecting several objects and selecting the target object. Proposed algorithm first detects some objects distributed in the image using focus measure operator and multi-window and then selects the target object through fuzzy reasoning with three fuzzy membership functions. Implementation can be simple because it only needs image sensor instead of infrared or ultrasonic equipment. Experimental result shows that the proposed algorithm can improve the quality of image by focusing to the target object.

Optimal Design Method of Quantization of Membership Function and Rule Base of Fuzzy Logic Controller using the Genetic Algorithm (유전자 알고리즘을 이용한 퍼지논리 제어기 소속함수의 양자화와 제어규칙의 최적 설계방식)

  • Chung Sung-Boo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.3
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    • pp.676-683
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    • 2005
  • In this paper, we proposed a method that optimal values of fuzzy control rule base and quantization of membership function are searched by genetic algorithm. Proposed method searched the optimal values of membership function and control rules using genetic algorithm by off-line. Then fuzzy controller operates using these values by on-line. Proposed fuzzy control system is optimized the control rule base and membership function by genetic algorithm without expert's knowledge. We investigated proposed method through simulation and experiment using DC motor and one link manipulator, and confirmed the following usefulness.

A Design on Collision Avoidance System of Vehicle using Fuzzy Control Algorithms (퍼지제어 알고리즘을 이용한 차량의 충돌방지 시스템 설계)

  • Choo, Yeon-Gyu;Kim, Seung-Cheo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.705-709
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    • 2005
  • In this paper, we introduce fuzzy algorithm similar to human's way of thinking and designed collision detection system of vehicles. First, before the model vehicles design, we did simulation collision detection using PID and Fuzzy Controller. As a result, P.O that is Percent Overshoot when make use of PID controller happened from smallest 32% to 45%. But, In case of using fuzzy controller they produced about 10% in 7% in case use 25 rule. We designed model vehicles that introduce Auto Guided Vehicle(AGV) with confirmed result in simulation. We set Polaroid 6500 sensor on the front of model automobile because distinguish existence automobile to the head. And we composed motor drive part to run vehicles and 80C196KC processor for control movement of vehicles influenced on distance data of the front vehicles that receive from supersonic waves sensor. In case of using Fuzzy controller, last value percent error happened about maximum 15% in smallest 5%, and we confirmed that distance with front vehicles kept when state hold time is about maximum 16 seconds in smallest 10 seconds.

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Development of a Multiple Monitioring System for Intelligence of a Machine Tool -Application to Drilling Process- (공작기계 지능화를 위한 다중 감시 시스템의 개발-드릴가공에의 적용-)

  • Kim, H.Y.;Ahn, J.H.
    • Journal of the Korean Society for Precision Engineering
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    • v.10 no.4
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    • pp.142-151
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    • 1993
  • An intelligent mulitiple monitoring system to monitor tool/machining states synthetically was proposed and developed. It consists of 2 fundamental subsystems : the multiple sensor detection unit and the intellignet integrated diagnosis unit. Three signals, that is, spindle motor current, Z-axis motor current, and machining sound were adopted to detect tool/machining states more reliably. Based on the multiple sensor information, the diagnosis unit judges either tool breakage or degree of tool wear state using fuzzy reasoning. Tool breakage is diagnosed by the level of spindle/z-axis motor current. Tool wear is diagnosed by both the result of fuzzy pattern recognition for motor currents and the result of pattern matching for machining sound. Fuzzy c-means algorithm was used for fuzzy pattern recognition. Experiments carried out for drill operation in the machining center have shown that the developed system monitors abnormal drill/states drilling very reliably.

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Implementation of Stimulated Brillouin Scattering in Optical Fiber Sensor for Improved Stability by Using Neuro-Fuzzy Theory (뉴로-퍼지 알고리즘을 적용한 광파이버 유도 브릴루앙 산란 센서의 신뢰도 향상에 관한 연구)

  • Hwang, Kyoung-Jun;Yeom, Keong-Tae;Kim, Yong-Kab
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.1
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    • pp.92-97
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    • 2008
  • This is a research to apply 1310nm single-mode optical fiber to a temperature sensor. The existing study of optical fiber sensor is complicated because it was made with various equipment. To vary scattering, the variation of optical frequency is measured by using Bragg(lattice) or pulse generator and also bulk system is created by YAG laser but there were some difficulties creating experimental environment and it was a problem that the stability of measured data was low. The temperature sensor system using the suggested sBs(stimulated Brillouin scattering:sBs) from this research is much more simplified straight-line system. To improve the trust and accuracy of noises from optical frequency and unclear results, it was analysed by using Neuro-Fuzzy algorithm. we tried to get more correct data than existing system. sBs measure that optical frequency changed due to the variation of temperature. The analyzed change rate of outcome by Fuzzy theory is 1.1 MHz.

A Fuzzy Control of Autonomous Mobile Robot for Obstacle Avoidance (장애물 회피를 위한 자율이동로봇의 퍼지제어)

  • Chae Moon-Seok;Jung Tae-Young;Kang Suk-Bum;Yang Tae-Kyu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.9
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    • pp.1718-1726
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    • 2006
  • In this paper, we proposed a fuzzy controller and algorithm for efficiently obstacle avoidance in unknown space. The ultrasonic sensor is used for position and distance recognition of obstacle, and fuzzy controller is used for left and right wheels angular velocity control. The fuzzification is used singleton method and the control rule is each wheel forty-nine. The fuzzy inference is used simplified Mamdani's reasoning and defuzzification is used SCOG(Simplified Center Of Gravity). The computer simulation based on mobile robot modelling was performed for the capacity of fuzzy controller and the really applicable possibility revaluation of the proposed avoidance algorithm and fuzzy controller. As a result, mobile robot was exactly reached in target and it avoided obstacle efficiently.

A Study of Method and Algorithm for Stable Flight of Drone (드론의 안정화 비행을 위한 방법 및 알고리즘에 관한 연구)

  • Cha, Gyeong Hyeon;Sim, Isaac;Hong, Seung Gwan;Jung, Jun Hee;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.10 no.3
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    • pp.32-37
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    • 2015
  • Unmaned Aerial Vehical(UAV) is a flight which is automatically flying by remote control on th ground. However UAV has an advantage of control that is easy, but has an disadvantage of not hovering. By comparison, quadcopter which is one of the UAV is easily operated. Also quadcopter has hovering function and high stability. In this paper, we propose stable flight algorithm associated PID(proportional-integral-derivative) control with fuzzy contorl to implement stable quadcopter system. After getting a positioning information of the drone, This proposed system is implemented for stable flight through flight attitude control using gyro and acceleration sensor. We also propose the flight mode system to hover drone with GPS sensor.

Study on Mobile Robot's Navigation Problem Using Jacobian and Fuzzy Inference System (자코비안과 퍼지 추론 시스템을 이용한 이동로봇의 주행문제에 관한 연구)

  • Choi Gyu-Jong;Ahn Doo-Sung
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.6
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    • pp.554-560
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    • 2006
  • In this paper, we propose the topological map building method about unknown environment using the ultrasonic sensors. An ultrasonic sensor inherently has the range error due to the specular reflection. To decrease this error, we estimate the obstacle states(position and velocity) using the local minimum sensor values and Jacobian. Estimated states are used to avoid the obstacles and build the topological map similar to the type that human being memorizes an environment. When a mobile robot is faced with three problems(comer way, cross way and dead end), it senses the movable directions using FIS(Fuzzy Inference System). Among these directions, it can select the target direction using binary decision tree(Turn Side Selector). Proposed algorithm has been verified with three simulations and three implementations.

An Intelligent Clustering Mechanism by Fuzzy Logic Inference

  • Pascalia Handayani;Young-Taek Kim
    • Annual Conference of KIPS
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    • 2008.11a
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    • pp.1039-1042
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    • 2008
  • Wireless sensor networks enable pervasive, ubiquitous, and seamless communication with the physical world. In this paper, we are concerned for clustering sensors into groups, so that sensors communicate information only to cluster heads and then the cluster heads communicate the aggregated information to the sink node, that the network can save energy. In this paper, we propose the algorithm for electing the cluster head and fuzzy registration of cluster head in a dynamic cluster wireless sensor networks. For making decision for clustering we will use fuzzy logic system. In simulation, we could achieve power regulation of total consumption and also the stabilization of the networks energy efficiency.