• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.91-96
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• 2003

The forces and moments at the aircraft c.g. have components due to aerodynamic effects and to engine thrust. For the flight stability and autopilot systems we present a attitude control method using an intelligent control algorithm Which is based on the control rules from experts knowledge concerning the motion equations and other experiences. Then a robust fuzzy controller is developed to control the flight attitude. The controller can deal with multiple inputs and outputs. We have made an aircraft model and the orientation sensor for experimental flights. The control rules based on the flight expert s experience and knowledge can be programmed by fuzzy rules, and determined control rules by experimental flight. We can be stable attitude control by fuzzy controller.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.257-260
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• 2007

In this paper addresses the low-level behavior of fuzzy control and the high-level behavior selector for Autonomous Mobile Robots (AMRs) based on a Fuzzy Artificial Immune Network. The sensing information that comes from ultrasonic sensors is the antigen it, and stimulates antibodies. There are many possible combinations of actions between action-patterns and external situations. The question is how to handle the situations to decide the proper action. We propose a fuzzy artificial immune network to solve the above problem. and the computer simulation for an AMR action selector shows the usefulness of the proposed action selector.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2083-2089
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• 2007

In this paper addresses the low-level behavior of fuzzy control and the high-level behavior selector for Autonomous Mobile Robots(AMRs) based on a Fuzzy Artificial Immune Network. The sensing information that comes from ultrasonic sensors is the antigen it, and stimulates antibodies. There are many possible combinations of actions between action-patterns and external situations. The question is how to handle the situations to decide the proper action. We propose a fuzzy artificial immune network to solve the above problem. and the computer simulation for an AMR action selector shows the usefulness of the proposed action selector.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.50-58
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• 2017

Recently, some methods of converging heterogeneous fire sensor data have been proposed for effective fire detection, but the rule-based methods have low adaptability and accuracy, and the fuzzy inference methods suffer from detection speed and accuracy by lack of consideration for images. In addition, a few image-based deep learning methods were researched, but it was too difficult to rapidly recognize the fire event in absence of cameras or out of scope of a camera in practical situations. In this paper, we propose a novel fire detection system combining a deep learning algorithm based on CNN and fuzzy inference engine based on heterogeneous fire sensor data including temperature, humidity, gas, and smoke density. we show it is possible for the proposed system to rapidly detect fire by utilizing images and to decide fire in a reliable way by utilizing multi-sensor data. Also, we apply distributed computing architecture to fire detection algorithm in order to avoid concentration of computing power on a server and to enhance scalability as a result. Finally, we prove the performance of the system through two experiments by means of NIST's fire dynamics simulator in both cases of an explosively spreading fire and a gradually growing fire.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.299-305
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• 2015

Modbus is a serial communications protocol, it has since become a practically standard communication protocol, and it is now a commonly available means of connecting industrial electronic devices. Therefore, it can be connected with all devices using Modbus protocol to the measurement and remote control on the ships, buildings, trains, airplanes and etc.. In this paper, we add the Modbus communication protocol to the existing lighting controller sensitivity to enable verification and remote control by external environmental factors, and also introduces a fuzzy inference system was configured by external environmental factors to control LED lighting. External environmental factors of temperature, humidity, illuminance value represented by the LED through a fuzzy control algorithm, the values accepted by the controller through the sensor. Modbus is using the RS485 Serial communication with other devices connected to the temperature, humidity, illumination and LED output status check is possible. In addition, the remote user is changed to enable it is possible to change the RGB values in the desired color change. Produced was confirmed that the LED controller output is based on the temperature, humidity and illumination.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.169-172
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• 2010

유비쿼터스 화재 방재 시스템은 온도, 습도, 조도, 가속도, CO2, 등의 다양한 센서로부터 얻는 값을 이용해 화재를 판별하여 관리자에게 전달하고 시스템 설정 값에 따라 소화설비를 동작시키는 지능형 화재 탐지 시스템이다. 기존 화재 판별 기법은 크게 영상인식, 퍼지추론, 베이지안 추론으로 나뉠 수 있다. 본 논문에서는 앞선 기술들을 분석하고, ARM9 S3C2440/SHT-75를 이용한 센서기반 유비쿼터스 화재 방재 시스템 최적의 화재 판별 기술로서 가속도 알고리즘과 벡터 랜덤변수 표본공간 영역을 이용한 패턴인식 기술을 사용한 복합 화재 판별 방법을 제안한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.533-539
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• 2012

The purpose of this study is to estimate a validity of control signal through a design of Exoskeleton Robot Arm's capable of intelligent recognition as a human arm's motion by using realtime processed data of generated EMG signals. By an intelligent algorithm, the EMG output value of human biceps and triceps muscles contraction can be recognized and used for the control over exoskeleton arm corresponding to human's recognition and judgement. The EMG sensing data of muscles contraction and relaxation are used as the input signal from human's body to operate the Exoskeleton Robot Arm thus copying human arm motion. An intelligent control of Exoskeleton Robot Arm is to design the analog control circuit which processes the input data, and then to manufacture an integrated control board. And then abstracted signal is passed by DSP signal processing, Fuzzy logic algorithm is designed for a accurate prediction of weight or load through the intelligent algorithm, and design an Exoskeleton Robot Arm to express a human's intention.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.190-195
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• 2007

As Ubiquitous era comes, it became necessary to construct environment which can provide more useful information to human in the spaces where people live like homes or offices. On this account, network of the peripheral devices of Ubiquitous should constitute efficiently. For it, this paper researched human pattern by classified motion recognition using sensors module data. (This data processing by Neural network and fuzzy algorithm.) This pattern classification can help control home network system communication. I suggest the system which can control home network system more easily through patterned movement, and control Ubiquitous environment by grasp human's movement and condition.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.299-302
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• 2019

스마트홈 구축을 위한 다양한 IoT 기술 발전과 더불어 IoT 장비들의 저전력, 고효율, 편리성에 대한 사용자 니즈에 대한 관심이 급증하고 있다. 이러한 사용자 니즈를 반영하듯이 최근 아두이노 및 라즈베리 파이등 저비용으로 IoT 장비를 구축할 수 있는 다양한 연구들이 진행되고 있다. 우리는 본 연구를 통해 뉴로-퍼지기술을 이용해 저전력, 고효율, 편리성을 겸비한 저렴한 IoT 장비 및 솔루션을 제안하고자 한다. 뉴로-퍼지를 이용하게 되면 기존의 단순한 센싱에 대한 제어와 다르게 다양한 환경변수를 분석하고 고려해 효율적인 제어가 가능할 수 있다. 본 논문에서는 욕실 환경에서의 발생할 수 있는 다양한 환경변수를 추출하고 사용자가 편리하게 사용할 수 있도록 실시간 발생하는 상황과 온도, 습도 등을 뉴로-퍼지를 통해 제어할 수 있는 알고리즘을 설계한다. 그리하여 뉴로-퍼지를 이용하여 설계된 욕실환경 제어 시스템은 사용자의 욕실 이용에 효과적인 영향을 줄 수 있을 것이다. 우리는 본 연구에서 저비용 고효율의 효율적 시스템을 구성할 수 있는 IoT 센서와 아두이노 및 라즈베리 파이를 활용해 다양한 IoT 장비들을 모니터링하고 분석하여 쾌적한 스마트 홈을 구축할 수 있는 방향을 제시하였다. 또한 그러한 IoT 장비들을 제어할 수 있는 IoT gateway system을 설계하고 구현하였다.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3039-3041
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• 1999

본 연구에서는 과수원에서 사용되는 농약살포용 스피드 스프레이어기(SS기)의 자율주행을 위한 시스템을 개발하였다. 과거의 SS기의 자율주행을 실현한 시스템은 대부분 고가의 장비를 사용하거나 실용성이 결여된 점에 비추어 본 연구에서는 실용가능성에 역점을 두어서 저가의 실용 가능한 시스템을 구성하고자 하였다. 개발된 자율주행 시스템의 특징으로는 1) 하드웨어 시스템을 고성능 프로세서를 이용하여 중앙집중식으로 개발 하였으며 2) 초음파센서의 보정 및 보강을 통해서 오차를 최소화하는 알고리즘을 개발하였으며 3) 현장에서 사용시 진동등의 noise에 강한 robust 시스템을 구성하였으며 4) 자율주행을 제어하기 위해서 퍼지알고리즘을 도입한 지능제어를 실현하였다.