• 전자공학회논문지B
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• 제29B권11호
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• pp.120-129
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• 1992

In this paper we propose a fuzzy-neural network(FNN) which includes both advantages of the fuzzy logic and the neural network. The basic idea of the FNN is to realize the fuzzy rule-base and the process of reasoning by neural network and to make the corresponding parameters be expressed by the connection weights of neural network. After constructing the FNN, a novel controller consisting of a conventional P-controller and a FNN is explained. In this control scheme, the rule-base of a FNN are automatically generated by error back-propagation algorithm. Also the parallel connection of the P-controller and the FNN can guarantee the stability of a plant at initial stage before the rules are completely created. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a 2 degree of freedom robot manipulator.

• 한국산업융합학회 논문집
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• 제18권4호
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• pp.259-266
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• 2015

This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.

• 전자공학회논문지B
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• 제32B권8호
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• pp.1119-1126
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• 1995

The construction of rule-base for a nonlinear time-varying system, becomes much more complicated because of model uncertainty and parameter variations. Furthemore, FLC does not have an ability of adjusting rule- base in responding to some sudden changes of control environments. To cope with these problems, an auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), which is known to be very effective in the optimization problem, will be proposed. The tuning of the proposed system is performed by two tuning processes(the course tuning process and the fine tuning/adaptive learning process). The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1235-1239
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• 2003

On the base of network frame and protocol system of Ethernet the networked sensing technology based on Ethernet is studied and the design principles of industrial Ethernet measurement of control system is put forward, and the general structure model is built in the paper. An eight-bit economical MCU scheme is proposed, and a general scheme of distributed intelligent networked measuring and control equipment based on TCP/IP is designed too. A compact TCP/IP protocol stack are successfully implemented in eight-bit MCU. With C51 program language, method of modularized programming is applied in soft design. The problem of in-system modifying measuring and control strategy of its system is solved successfully by assigning memory dynamically and saving parameter with EEPROM, and it makes the intelligent networked measurement and control system can explain and analyses control strategy from PC. Experiment result shows that, the research of intelligent networked measurement and control equipment and system base on TCP/IP is successful, with flexible network, convenient usage, and good commonality.

• 정보화연구
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• 제11권2호
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• pp.157-173
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• 2014

기지방어, 대공방어 그리고 화생방방호 모델은 공군의 지상 작전 모델로써 참가 노드간 음성통신 중심의 체계로 설계되어 있어 정확한 의사전달에 문제가 있다. 이러한 문제를 해결하기 위해 최근 국방 분야에서는 데이터통신 기술을 이용하여 지휘통제 능력을 향상시키고 있다. 본 논문에서는 데이터통신에 기반한 차세대 기지방어작전 모델을 통해 기지방어 임무 성능향상을 극대화할 수 있는 새로운 모델을 제안한다. 현재까지 연구된 논문을 참고하여 새로운 모델을 개발하였고, 제안한 기지방어작전 모델을 비행기지내에 기존 정비통제용으로 구축되어 있던 와이브로 네트워크상에서 적용하여 실제실험을 하였다. 새로운 기지방어작전 모델의 분석 및 실험 결과 본 논문에서 제안한 모델이 성능개선에 효과가 있다는 결론에 도달한다.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제5권4호
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• pp.87-94
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• 2016

제안된 논문은 기지국의 에너지 효율을 최대화하기 위한 에너지 전송 방식에 관한 것으로, 기존의 데이터 처리량과 송신전력 사이의 지수 함수적 관계에 따른 비효율적 문제를 해결함으로써 서비스의 유형에 따른 데이터를 분류하고, 무선 네트워크 환경의 기지국에서 사용자 들에게 전송 되는 최적의 데이터 량에 따른 에너지 최적화 지점을 찾아내는 방법이다. 이를 위해, 기지국에서 사용자에게 전송되는 데이터의 양 및 유지시간을 조절하여 데이터 전송의 에너지 효율 최적화 지점을 찾을 수 있는 EETA 알고리즘(Energy-Efficient Transmission Algorithm)을 제안한다. 결과적으로 제안한 방식은 기존 기지국 대비 에너지 효율이 약 10% 향상됨을 알 수 있다.

• 정보학연구
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• 제4권2호
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• pp.117-127
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• 2001

본 논문에서는 퍼지모델의 최적 입-출력 소속함수들(membership functions) 및 규칙기반(rulebase) 얻기 위한 자율가변구조의 신경망 알고리즘을 제안하였으며 구륜 이동 로봇(WMR : Wheeled Mobile Robot)의 위치, 속도 방향제어를 위한 퍼지-신경망 제어기 설계를 설계하였다. 제안된 알고리즘에서 입-출력 소속함수의 파라미터들을 찾기 위하여 유전알고리즘을 응용한다. 유전알고리즘에 의해 출력술어의 원소가 증가되며, 규칙기반이 원소의 증가에 의하여 조절된다. 새롭게 조절된 제어기는 출력술어의 증가를 수행하지 않은 제어기와 경쟁하며. 만약 새롭게 조절되어진 퍼지-신경망 제어기가 경쟁에서 진다면, 그 제어법칙은 소멸한다. 그 반대로 조절된 제어기가 생존한다면, 출력술어의 증가된 각 원소들 및 변화된 시스템의 규칙기반이 제어기에 적용된다. 출력술어 및 규칙의 조절이 완료된 후 입력소속함수들에 대한 탐색이 제약조건을 가지고 수행되며 입력소속함수들의 탐색이 완료된 후 출력소속함수의 미세 조정이 수행된다.

• 제어로봇시스템학회논문지
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• 제12궈1호
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• pp.60-65
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• 2006

Recently, various ubiquitous networking services are developed and implemented for easy living. In general, new ubiquitous networking services require the new infrastructure including equipments and devices. However, it is difficult to replace existing infrastructure and devices with new ones in the home or office because of cost and maintenance problems. In this paper, we developed small-size web based RF wireless communication systems for sensor network applications. The designed RF systems are implemented using commercial system on a chip (SoC) on existing infrastructure and devices. The developed systems are tested for light control and temperature sensing and they are applied to sensor network training courses for students and engineer as well as various practical applications.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.1703_1704
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• 2009

Fuzzy neural ship controllers is used in ship steering control. It can make full use of the advantage of all kinds of intelligent algorithms. This provides an efficient way for this paper. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors. Utilizing the designed network to substitute the conventional fuzzy inference, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The ship control quality is effectively improved in case of appending additional sea state disturbance. The performance of controller is evaluated by the system simulation using simulink tools.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 제39회 하계학술대회
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• pp.671-672
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• 2008

Hybrid intelligent technique is used in ship steering control. It can make full use of the advantage of all kinds of intelligent algorithms. This provides an efficient way for this paper. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors. Utilizing the designed network to substitute the conventional fuzzy inference, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The ship control quality is effectively improved in case of appending additional sea state disturbance. The performance of controller is evaluated by the system simulation using Matlab.