• 한국ITS학회 논문지
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• 제5권1호
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• pp.21-30
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• 2006

중앙버스전용차로제가 도입됨에 따라 서울의 도로환경은 단기간에 급격하게 변하였으며, 이러한 급격한 변화에 미리 준비되지 못하였던 신호운영상의 문제점들이 경험되고 있다. 장 임계적인 문제점으로 중앙버스전용차로 설치구간 신호교차로에서 일반차량 좌회전 진행을 허용할 경우, 현재 우리나라가 규정하고 있는 차량 4색신호등의 한계로 인한 신호의 비효율적 운영이다. 중앙버스전용차로 설치구간 신호교차로에서 일반차량 좌회전의 현실적 운영방안 마련이 필요하다. 본 연구는 중앙차로전용신호의 도입을 준비하기 위하여 교통관제센터의 신호운영모드별 선행좌회전 및 후행좌회전 운영방안을 검토하고, 각 운영방안 별 Signal Map 구성방안을 점검한다. Signal Map 작성방안을 검토한 결과 기존의 신호제어 장비에 추가의 신호등기신호보드를 활용하는 방법으로 제안된 방법의 현장 적용이 용이한 것으로 확인되었다.

• 한국ITS학회 논문지
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• 제11권5호
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• pp.116-124
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• 2012

본 논문에서는 AVR 기반의 LSDM 제어를 위한 효율적인 점등제어 시스템 설계를 제안한다. 본 논문은 LSDM 제어을 위한 효율적인 점등제어 시스템의 설계는 I/O 데이터 버스를 위한 신호 제어부와 동작 상태에 따른 클록 신호 제어를 위한 타이머/카운터부로 구분하여 설계한다. LSDM 제어로직은 효율적인 제어신호 처리를 위하여 각 비트에 논리 값을 지정하여 DDRx와 PORTx 레지스터를 최적화한다. 그리고 ATmega128의 점등제어 프로그램 실행에 의한 LSDM 제어신호는 제어로직을 동작시켜 LSDM 점등제어가 가능하도록 설계한다. 본 논문에서 제안한 점등제어 시스템은 전력 손실률 감소효과를 입증하기 위하여, 호스트 PC에서 시리얼을 통해 점등제어 프로그램을 시스템에 다운로드하여 LSDM 제어로직의 점등 상태에 대한 전력 손실률을 측정하였다. 측정한 결과, 기존의 점등제어 시스템보다 제안한 점등제어 시스템은 전체적인 전력 소모 감소 효과가 있음을 입증하였다.

• Journal of Advanced Marine Engineering and Technology
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• 제20권3호
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• pp.286-286
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• 제20권3호
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권2호
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• pp.251-257
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• 2003

In this paper, we wish to construct a optimal traffic cycle using wire remote control. if police vehicle or ambulance suddenly enter the traffic Intersection, it will increase the traffic accident. In this paper, wireless traffic light use the radio traffic control signal and research about the hardware manufacture to check special detectors on urgency vehicles may safety and rapidly enter traffic intersection. Also, this paper present a traffic signal control conditions that analyzes different traffic intersection flows in cases of saturated flows, where the real traffic volume demand is large and the capacity constraints of bottlenecks have significant effects on the flow patterns. Through computer simulation this wireless traffic light has been proven to be much more safety and efficient than fixed traffic signal light which does not consider emergency vehicles for safety escort.

• 한국ITS학회 논문지
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• 제10권4호
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• pp.100-106
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• 2011

무선통신환경에서는 RF신호가 매우 심하게 변하는데, 이러한 신호의 변화는 특히 차량통신환경에서 더욱 심해진다. 자동이득제어는 무선통신시스템에서 신뢰성 있는 통신환경을 제공하고 급격하게 변하는 수신신호를 보상하데 중요한 역할을 한다. 본 논문에서는 수신신호세기값과 아날로그-디지털변환값 두 가지 신호를 이용하는 간단하고 향상된 자동이득 제어기법에 대해 논의한다. 시물레이션과 실제 환경에의 측정을 통해 제안된 기법의 성능을 검증한다.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2005년도 춘계학술대회논문집
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• pp.319-324
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• 2005

The interface between host processor and the ShortStack Micro Server may be a Serial Communication Interface(SCI). The LonWorks control module with a high performance is developed, which is composed of the 8 bit PIC Microprocessor for host processor and the smart neuron chip for the ShoretStack Micro Server. This intelligent control board is verified as proceeding the various function tests from experimental system with an boost pump and inverter driving systems. It is also confirmed that the developed control module provides stably 0-10VDC linear signal to the input signal of inverter driving system for varying the induction motor speed. Thus, the experimental results show that the fabricating intelligent board carried out very well the various functions in the wide operating ranges of boost pump system. This developed control module expect to apply to industrial fields to require the comparatively exact control and monitoring such as multi-motor driving system with inverter, variable air volume system and the boost pump water supply systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.942-947
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• 2003

An important signal processing problem in PVDF sensor is the restoration of surface information from electric sensing signals. The objectives of this research are to design a new texture sensing system and to develop a new signal processing algorithm for signals from the sensor to be tangibly displayed by tangible interface systems. The texture sensing system is designed to get surface information with high resolution and dynamic range. First, a PVDF sensor is made of piezoelectric polymer (polyvinylidene fluoride) strips molded in a silicon rubber and attached in a rigid cylinder body. The sensor is mounted to a scanning system for dynamic sensing. Secondly, a new signal processing algorithm is developed to restore surface information. The algorithm consists of the two-dimensional modeling of the sensor using an identification method and inverse filtering from sensing signals into estimated surface information. Finally the two-dimensional surface information can be experimentally reconstructed from sensing signals using the developed signal processing algorithm.

• 한국ITS학회:학술대회논문집
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• 한국ITS학회 2004년도 제3회 정기총회 및 추계학술대회
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• pp.149-153
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• 2004

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.614-619
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• 2004

The line-of-sight (LOS) stabilization system is a precision electro-mechanical gimbals assembly for rejecting vibration to isolate the load from its environment and point toward the target in a desired direction. This paper describes the design of gimbals system to reject the disturbance and to improve stabilization. To generate movement commands for the actuators in the stabilization system, the control system uses a sensor of angular rotation. The controller is a DSP with transducer and actuator interfaces. Unknown parameters of the gimbals are estimated using the signal compression method. The cross-correlation coefficient between the impulse response from the assumed model and the one from model of the gimbals is used to obtain the better estimation. And SMCPE (sliding mode control with perturbation estimation) is used to control the gimbals. SMCPE provides robustness of the control against the modeling deficiencies and unknown disturbances. In order to compare the performance of SMCPE with the classical SMC, a sample test result is presented.