• 제목/요약/키워드: Control signal

검색결과 6,355건 처리시간 0.034초

반구형 공진 자이로스코프의 신호 검출 및 제어 (Signal Detection and Control of Hemispherical Resonator Gyroscopes)

  • 현철;강태삼
    • 센서학회지
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    • 제21권3호
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    • pp.204-210
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    • 2012
  • In this paper, signal detection and control circuits for hemispherical resonator gyroscope(HRG) are designed, simulated and tested. HRG is one of the coriolis vibratory gyroscope(CVG) which has very stable quartz hemispherical resonator and shows very precise performance. HRG signals are usually modulated at the several kHz of resonant frequency. So the general control scheme cannot be applied directly because general control schemes mainly focused at low frequency range. Using demodulated and modulated PI control scheme with the signal detection which is presented in this paper, performance of manufactured HRG has tested.

단독운전 모드 동작에서의 Triple-Active-Bridge 컨버터 제어 기법 및 소신호 모델을 기반으로 한 제어기 설계 (Control Technique of Triple-Active-Bridge Converter and Its Effective Controller Design Based on Small Signal Model for Islanding Mode Operation)

  • 전찬오;허경욱;류명효;정지훈
    • 전력전자학회논문지
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    • 제27권3호
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    • pp.192-199
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    • 2022
  • In DC distribution systems, a TAB converter employing multiple transformers is one of the most widely used topologies due to its high power density, modularizability, and cost-effectiveness. However, the conventional control technique for a grid-connected mode in the TAB converter cannot maintain its reliability for an islanding mode under a blackout situation. In this paper, the islanding mode control technique is proposed to solve this issue. To verify the relative stability and dynamic characteristics of the control technique, small-signal models of both the grid connected and the islanding mode are derived. Based on the small-signal models, PI controllers are designed to provide suitable power control. The proposed control technique, the accuracy of small-signal models, and the performance of the controllers are verified by simulations and experiments with a 1-kW prototype TAB converter.

선형회기분석을 이용한 고장분포 추정에 관한 연구 (Study on the Failure Distribution Estimation using Linear Regression Analysis)

  • 이강미;신덕호;백종현;이재호
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2008년도 하계종합학술대회
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    • pp.1109-1110
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    • 2008
  • It is required to optimize the system operation efficiency to allocate maintenance task and period using systemic maintenance process. To allocate maintenance task and period must analysis the failure distribution mode at first. In this paper, we introduce the linear regression analysis and estimate the failure distribution for the railroad signal equipment using that.

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DSP 소프트웨어에 의한 전력변환기 게이팅 신호 발생 (Power Converter Gating Signal Generation with DSP Software)

  • 이해춘;박태열;김기택
    • 산업기술연구
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    • 제21권A호
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    • pp.111-116
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    • 2001
  • Power converters are widely used in the applications of servo drives of ac and dc motors and power supplies. For the control of the converters carious control algorithms have been proposed and realized by gating signal generation. Software control shemes are being applied to implement the control algorithms, but analog circuits are still used for the gating signal generation because it requires very fast and precise timing. In this paper the gating signal generation with DSP software are proposed for the three phase to three phase PWM converter. Design procedures and software flowcharts are presented and some experimental waveforms are also presented to verify the proposed algorithms.

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Reinforcement Learning Control using Self-Organizing Map and Multi-layer Feed-Forward Neural Network

  • Lee, Jae-Kang;Kim, Il-Hwan
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.142-145
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    • 2003
  • Many control applications using Neural Network need a priori information about the objective system. But it is impossible to get exact information about the objective system in real world. To solve this problem, several control methods were proposed. Reinforcement learning control using neural network is one of them. Basically reinforcement learning control doesn't need a priori information of objective system. This method uses reinforcement signal from interaction of objective system and environment and observable states of objective system as input data. But many methods take too much time to apply to real-world. So we focus on faster learning to apply reinforcement learning control to real-world. Two data types are used for reinforcement learning. One is reinforcement signal data. It has only two fixed scalar values that are assigned for each success and fail state. The other is observable state data. There are infinitive states in real-world system. So the number of observable state data is also infinitive. This requires too much learning time for applying to real-world. So we try to reduce the number of observable states by classification of states with Self-Organizing Map. We also use neural dynamic programming for controller design. An inverted pendulum on the cart system is simulated. Failure signal is used for reinforcement signal. The failure signal occurs when the pendulum angle or cart position deviate from the defined control range. The control objective is to maintain the balanced pole and centered cart. And four states that is, position and velocity of cart, angle and angular velocity of pole are used for state signal. Learning controller is composed of serial connection of Self-Organizing Map and two Multi-layer Feed-Forward Neural Networks.

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멀티 에이전트를 이용한 도로정체에 따른 교통흐름 예측 및 통합제어 (The Integrated Control Model for the Freeway Corridors based on Multi-Agent Approach)

  • 조기용;배철호;이정환;주열;서명원
    • 한국자동차공학회논문집
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    • 제14권5호
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    • pp.84-92
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    • 2006
  • Freeway Corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. Optimization results are verified by comparison with the results from MATDYMO.

멀티 에이전트를 이용한 도로정체에 따른 교통흐름 예측 및 통합제어 I : 시뮬레이션 시스템 개발 및 최적화를 위한 모델링 (The Integrated Control Model for the Freeway Corridors based on Multi-Agent Approach I : Simulation System & Modeling for Optimization)

  • 조기용;배철호;김현준;주열;서명원
    • 한국자동차공학회논문집
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    • 제15권1호
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    • pp.8-15
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    • 2007
  • Freeway corridors consist of urban freeways and parallel arterials that drivers can use alternatively. Ramp metering in freeways and signal control in arterials are contemporary traffic control methods that have been developed and applied in order to improve traffic conditions of freeway corridors. However, most of the existing studies have focused on either optimal ramp metering in freeways, or progression signal strategies between arterial intersections. There have been no traffic control systems in Korea that integrates the freeway ramp metering and arterial signal control. The effective control strategies for freeway operations may cause negative effects on arterial traffic. On the other hand, traffic congestion and bottleneck phenomenon of arterials due to the increasing peak-hour travel demand and ineffective signal operation may generate an accessibility problem to freeway ramps. Thus, the main function of the freeway which is the through-traffic process has not been successful. The purpose of this study is to develop an integrated control model that connects freeway ramp metering systems and signal control systems in arterial intersections. And Optimization of integrated control model which consists of ramp metering and signal control is another purpose. The design of experiment, neural network, and simulated annealing are used for optimization.

LabView를 이용한 자동유량제어 시스템의 개발 (Development of automatic flow control system based on LabView)

  • 강태원;김두섭;안승규
    • 공학교육연구
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    • 제19권2호
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    • pp.3-7
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    • 2016
  • A flow control system was designed and fabricated to control the flow rate of liquid through the pipe. This control system was composed of hardwares and software, hardwares as controller, gate valve, orifice meter and data aquisition board and software as National instruments Labview program. Control of flow rate was executed by adjusting the pneumatic valve located at the center of pipe line based on the control signal generated by LabView PID control algorithm, which converts analog signal measured by pressure difference of orifice to digital signal to adjust pneumatic valve. For the controller setup Ziegler-Nichols tuning technique was applied and control performances were investigated for not only the disturbance but also the set point changes. Developed system showed good control performances in flow control enough to use as teaching tool of feedback control theory and practice in university, and also as industrial application.

디지털 시그널 프로세서를 이용한 스카라 로봇의 적응-신경제어기 설계 (Design of Adaptive-Neuro Controller of SCARA Robot Using Digital Signal Processor)

  • 한성현
    • 한국생산제조학회지
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    • 제6권1호
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    • pp.7-17
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    • 1997
  • During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

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약 신호 환경에서의 Assisted-Galileo 신호 획득 성능 분석 (Performance Analysis of Assisted-Galileo Signal Acquisition Under Weak Signal Environment)

  • 임정민;박지원;성태경
    • 제어로봇시스템학회논문지
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    • 제19권7호
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    • pp.646-652
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    • 2013
  • EU's Galileo project is a market-based GNSS (Global Navigation Satellite System) that is under development. It is expected that Galileo will provide the positioning services based on new technologies in 2020s. Because Galileo E1 signal for OS (Open Service) shares the same center frequency with GPS L1 C/A signal, CBOC (Composite Binary Offset Carrier) modulation scheme is used in the E1 signal to guarantee interoperability between two systems. With E1 signal consisting of a data channel and a pilot channel at the same frequency band, there exist several options in designing signal acquisition for Assisted-Galileo receivers. Furthermore, compared to SNR worksheet of Assisted-GPS, some factors should be examined in Assisted-Galileo due to different correlation profile and code length of E1 signal. This paper presents SNR worksheets of Galileo E1 signals in E1-B and E1-C channel. Three implementation losses that are quite different from GPS are mainly analyzed in establishing SNR worksheets. In the worksheet, hybrid long integration of 1.5s is considered to acquire weak signal less than -150dBm. Simulation results show that the final SNR of E1-B signal with -150dBm is 19.4dB and that of E1-C signal is 25.2dB. Comparison of relative computation shows that E1-B channel is more profitable to acquire the strongest signal in weak signal environment. With information from the first satellite signal acquisition, fast acquisition of the weak signal around -155dBm can be performed with E1-C signal in the subsequent satellites.