• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.477-477
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• 2000

A multifunctional sensor is designed to measure viscosity, cleanness, temperature and capacitance of engine oil to make a clear decision on its condition. The simple structure helps easy fabrication and low cost while measuring four parameters by one sensor. The operation is described theoretically and is supported by experimental data. A fuzzy based algorithm to fuse the four kinds of data from multi-functional sensor in order to make a decision on the best time to change the oil is proposed.

• 한국군사과학기술학회지
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• 제13권3호
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• pp.445-452
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• 2010

Adequate segmentation of target objects from the background plays an important role for the performance of automatic target recognition(ATR) system. This paper presents a new segmentation algorithm using fuzzy thresholding to extract a target. The proposed algorithm consists of two steps. In the first step, the region of interest(ROI) including the target can be automatically selected by the proposed robust method based on the frame difference of each image sensor. In the second step, fuzzy thresholding with a proposed membership function is performed within the only ROI selected in the first step. The proposed membership function is based on the similarity of intensity and the adjacency of target area on each image. Experimental results applied to real CCD/IR images show a good performance and the proposed algorithm is expected to enhance the performance of ATR system using multi-sensors.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.583-586
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• 1995

In this paper, a nor fuzzy control algorithm for the target tracking system is proposed, and its characteristics are analyzed and compared with those of the traditional PID controller. Fuzzy rules are generated experimentally using Mamdani's minimum operation and the center of area method. The experimental results prove that the proposed fuzzy algorithm is excellent in our tracking system and its performance is superior to that of the PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.694-697
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• 1996

The aim of this work for 5 years from 1994 is to develop a multi-fingered robot hand and its control system for grasp and manipulation of objects dexterously. Since the robot hand is still being developed, a commercialized robot hand from Barrett Company is utilized to implement a hand controller and control algorithm. For this, VME based motion control and interface boards are developed and multi-sensors such as encoder, force/torque sensor, dynamic sensor and artificial skin sensor are partly developed and employed for the grasping control algorithm. In oder to handle uncertainties such as mechanical idleness and backlash, a fuzzy rule based grasping algorithm is also considered and tested with the developed control system.

• 한국전자통신학회논문지
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• 제18권1호
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• pp.53-62
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• 2023

최근 신재생에너지 증가로 인하여 가스터빈 발전기는 양질의 전력공급을 위해 일일 기동·정지가 지속되고 있으며 이에 따른 영향으로 고온부품의 수명이 단축되고 고온 측정용 온도센서의 고장발생 빈도가 높아지고 있고 있다. 이에 본 연구에서는 가스터빈 제어에 사용되고 있는 듀얼 온도센서가 고장이 났을 경우 센서의 고장을 정확하게 진단하고 체계적으로 검출할 수 있는 퍼지로직 기반의 고장진단 알고리즘을 제안하였으며, 제안된 알고리즘의 유용성 확인을 위해 Matlab/Simulink의 환경에서 다양한 시뮬레이션을 수행함으로 제안된 알고리즘의 유용성을 확인하고자 하였다.

• 한국정밀공학회지
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• 제20권11호
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3515-3538
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• 2015

Data accuracy can be increased by detecting and removing the incorrect data generated in wireless sensor networks. By increasing the data accuracy, network lifetime can be increased parallel. Network lifetime or operational time is the time during which WSN is able to fulfill its tasks by using microcontroller with on-chip memory radio transceivers, albeit distributed sensor nodes send summary of their data to their cluster heads, which reduce energy consumption gradually. In this paper a powerful algorithm using proactive fuzzy system is proposed and it is a mixture of fuzzy logic with comparative correlation techniques that ensure high data accuracy by detecting incorrect data in distributed wireless sensor networks. This proposed system is implemented in two phases there, the first phase creates input space partitioning by using robust fuzzy c means clustering and the second phase detects incorrect data and removes it completely. Experimental result makes transparent of combined correlated fuzzy system (CCFS) which detects faulty readings with greater accuracy (99.21%) than the existing one (98.33%) along with low false alarm rate.

• 한국정보전자통신기술학회논문지
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• 제9권6호
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• pp.624-629
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• 2016

Recently various types of disaster monitoring system using smart-phones are under active studying. In this paper, we propose a system that automatically performs the disaster and fire detection. Additionally we implement the Arduino-based smart image sensor system in the web platform. When a fire is detected, an SMS is sent to the Fire and Disaster Management Agency. In order to improve fire detection probability, we proposed a smart Arduino fire detection sensor simulation which searches the smart sensor inference algorithm using fuzzy rules.

• 한국지능시스템학회논문지
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• 제18권2호
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• pp.163-168
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• 2008

이동로봇의 위치인식과 이를 바탕으로 하는 주행시스템은 이동로봇 핵심기술 중의 하나이다. 무선 센서 네트워크는 저전력, 저가, 단순성 등이 주된 특징으로서 실내 위치인식 시스템의 응용에 있어서 많은 가능성을 지니고 있다. 본 논문에서는 ZigBee 기반 무선 센서 네트워크에 퍼지 모델링 방법을 사용하여 이동로봇의 실내 위치인식 알고리즘을 구현하여 이를 주행시스템에 적용하고자 한다. ZigBee 기반 센서 네트워크에서는 노드들 간의 거리를 인식하기 위해서 RSSI (Received Signal Strength Indication) 값을 이용하게 된다. 그러나 이 RSSI 값은 건물 주위 물체에 의해 왜곡되거나 반사되는 수신 신호의 특성에 의해 영향을 받게 된다. 따라서 정확한 거리 정보를 알아내기 위해서는 적절한 교정 방법이 필요하며, RSSI 값에 퍼지 모델링 기법을 이용하여 정확한 거리 정보를 추출하고자 한다. 또한 이 거리 정보를 바탕으로 동적 삼각측량법을 이용하여 이동로봇의 실내 위치를 효율적으로 인식하고 주변 상항 변화에 효과적으로 대처할 수 있는 주행 알고리즘을 개발하고자 한다.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권7호
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• pp.437-442
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• 2005

In order to realize the speed control of an induction motor, the information of the rotor speed is needed. So the speed sensor as an encoder or a pulse generator is used to obtain it. But the use of speed sensor occur the some problems in the control system of an induction motor. To solve the problems, the appropriate speed estimation algorithm is used instead of the speed sensor. Also there is the limitation to improve the speed control performance of an induction motor using the existing speed estimation algorithm. Therefore, in this paper, intelligent speed estimator using Fuzzy-Neural systems as adaptive laws in Model Reference Adaptive System is proposed so as to improve the existing estimation algorithm and ,using the rotor speed estimated by the Proposed estimator, the speed control of an induction motor without speed sensor is performed. The computer simulation and the experiment is executed to prove the performance of the speed control system usinu the proposed speed estimator.