• Title/Summary/Keyword: Fuzzy Logic System

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Real-time EtherCAT Master Implementation on Xenomai for a Robot System

  • Moon, Yong-Seon;Ko, Nak-Yong;Lee, Kwang-Seok;Bae, Young-Chul;Park, Jong-Kyu
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.3
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    • pp.244-248
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    • 2009
  • This paper describes a real-time EtherCAT Master library. The library is developed using Xenomai. Xenomai is a real-time development framework. It cooperates with the Linux kernel, in order to provide a pervasive, interface-agnostic, hard real-time support to user-space applications, seamlessly integrated into the GNU/Linux environment. The proposed master library implements EtherCAT protocol for master side, and supports Application Programming Interfaces(APIs) for programming of real-time application which controls EtherCAT slave.

Context Aware System based on Bayesian Network driven Context Reasoning and Ontology Context Modeling

  • Ko, Kwang-Eun;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.4
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    • pp.254-259
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    • 2008
  • Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.

Analysis of Indoor Robot Localization Using Ultrasonic Sensors

  • Naveed, Sairah;Ko, Nak Yong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.1
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    • pp.41-48
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    • 2014
  • This paper analyzes the Monte Carlo localization (MCL) method, which estimates the pose of an indoor mobile robot. A mobile robot must know where it is to navigate in an indoor environment. The MCL technique is one of the most influential and popular techniques for estimation of robot position and orientation using a particle filter. For the analysis, we perform experiments in an indoor environment with a differential drive robot and ultrasonic range sensor system. The analysis uses MATLAB for implementation of the MCL and investigates the effects of the control parameters on the MCL performance. The control parameters are the uncertainty of the motion model of the mobile robot and the noise level of the measurement model of the range sensor.

Speed Control of BLDD Motor Using Neural Network based Adaptive Controller (신경 회로망을 이용한 BLDD 모터의 속도 적응 제어기)

  • Kim, Chang-Gyun;Lee, Joong-Hui;Youn, Myung-Joong
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.714-716
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    • 1995
  • This Paper presents a novel and systematic approach to a self-learning controller. The proposed controller is built on a neural network consisting of a standard back propagation (BNN) and approxinate reasoning (AR). The fuzzy inference and knowledge representation are carried out by the neural network structure and computing, instead of logic inference. An architecture similar to that used by traditional model reference adaptive control system (MRAC) is employed.

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The decision of the reference axis for the subjective estimation of X-Ray Images (X-선영상의 심리적 평가를 위한 판정기준축의 결정)

  • Lee, Yong-Gu;Lee, Sun-Yeob;Lee, Won-Seok;Eom, Ki-Hwan
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.439-440
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    • 2007
  • We determined the reference axis for the subjective estimation of X-ray images. The used images are the noised image and the noise plus signal image. The used subjective estimation method is the curve of Receiver Operation Characteristic. To determine the evaluation reference axis between the noise image and the image with signal, Fuzzy Logic System is used.

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A Reinforcement Learning with CMAC

  • Kwon, Sung-Gyu
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.4
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    • pp.271-276
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    • 2006
  • To implement a generalization of value functions in Adaptive Search Element (ASE)-reinforcement learning, CMAC (Cerebellar Model Articulation Controller) is integrated into ASE controller. ASE-reinforcement learning scheme is briefly studied to discuss how CMAC is integrated into ASE controller. Neighbourhood Sequential Training for CMAC is utilized to establish the look-up table and to produce discrete control outputs. In computer simulation, an ASE controller and a couple of ASE-CMAC neural network are trained to balance the inverted pendulum on a cart. The number of trials until the controllers are established and the learning performance of the controllers are evaluated to find that generalization ability of the CMAC improves the speed of the ASE-reinforcement learning enough to realize the cartpole control system.

Development of Interactive Feature Selection Algorithm(IFS) for Emotion Recognition

  • Yang, Hyun-Chang;Kim, Ho-Duck;Park, Chang-Hyun;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.4
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    • pp.282-287
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    • 2006
  • This paper presents an original feature selection method for Emotion Recognition which includes many original elements. Feature selection has some merits regarding pattern recognition performance. Thus, we developed a method called thee 'Interactive Feature Selection' and the results (selected features) of the IFS were applied to an emotion recognition system (ERS), which was also implemented in this research. The innovative feature selection method was based on a Reinforcement Learning Algorithm and since it required responses from human users, it was denoted an 'Interactive Feature Selection'. By performing an IFS, we were able to obtain three top features and apply them to the ERS. Comparing those results from a random selection and Sequential Forward Selection (SFS) and Genetic Algorithm Feature Selection (GAFS), we verified that the top three features were better than the randomly selected feature set.

An Application of Human-Centered Multimedia System for Medical Implementation

  • Ko, Je-Suk;Kitjongthawonkul, Somkiat
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.4
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    • pp.255-260
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    • 2009
  • Multimedia interpretation describes a high level of ion of multimedia content like interrelations and coherencies. In this paper, we describe a multimedia interpretation component from human-centered perspective. In this context, we see the role of the multimedia interpretation component as a liaison between the psychological apparatuses and computer-based artifact. We emphasize this role of multimedia interpretation by outlining a mapping process of the psychological apparatuses and computer-based artifact. This mapping process needs to be transparent to its user so that effective human-centered systems can be achieved. This transparency will provide an immersive environment for the users and enable uninhibited interaction between the users and the artifact. Furthermore, we illustrate how the multimedia interpretation component can be utilized in the medical diagnosis and treatment support application.

Task-Based Analysis on Number of Robotic Fingers for Compliant Manipulations

  • Kim, Byoung-Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.4
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    • pp.333-338
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    • 2009
  • This paper presents a task-based analysis on the number of independent robotic fingers required for compliant manipulations. Based on the stiffness relation between operational space and fingertip space of a multi-fingered object manipulating system, we describe a technique for modulation of the fingertip stiffness without inter-finger coupling so as to achieve the desired stiffness specified in the operational space. Thus, we provides a guide line how many fingers are basically required for successful multi-fingered compliant tasks. Consequently, this paper enables us to assign effectively the number of fingers for various compliant manipulations by robot hands.

A study on the speed control of the step motor for driving face-tracking camera (얼굴추적 카메라 구동에 사용된 스텝모터의 속도제어에 관한 연구)

  • Lee, J.B.;Sung, H.K.;Kim, Y.O.;Jeong, J.H.;Bom, J.H.
    • Proceedings of the KIEE Conference
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    • 2001.10a
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    • pp.230-232
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    • 2001
  • The camera system we researched has two stepping motors for the pan and tilt operation, and the human face tracking algorithm. Recently, this kind of the camera is used in PC communication, telecommunication vision meeting and tele-lecture. This paper discusses the smooth speed control method of this camera when the face is moved to up, down, left and right direction. We used a mean shift algorithm for the face-tracking, proposed the speed control algorithm using a fuzzy logic and certified this characteristics with the experiment.

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