• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.260-260
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• 2000

In this work, we have developed a 2 degree of freedom(DOF) motion simulator that can generate the sensation of motion in a 6 DOF space. The motion base has the DOF of roll and pitch, and the purpose of the motion base is to create the sensation of riding a vehicle in a 3D space by controlling the motion base. The dynamics of the mechanism was analysed and the optimal design of the motion base mechanism has been reached. The prototype motion base mechanism was developed and tested. The multi-axis motion controller(MMC) was used to control the two ac servo motors that drive the roll and pitch motion.

• 한국정보전자통신기술학회논문지
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• 제15권4호
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• pp.237-242
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• 2022

관제 및 측정 시스템 등에서 고품질 영상을 획득하는 것은 중요한 요소 중 하나이다. 영상 획득 기술 중에서 SFF (Shape from Focus)는 물체를 광축 방향으로 사전에 결정된 스텝 사이즈로 이동시킴으로써 초점 정도가 다른 2D 영상들을 획득함으로써 삼차원 형상을 복원하는 기술이다. SFF를 위해 일정한 스텝 사이즈로 물체를 이동시킬 때 각 스텝에서 광축 방향으로 기계 진동, 즉 지터 노이즈가 발생한다. 본 논문에서는 이 지터 노이즈의 영향을 줄이기 위해 새로운 상태 추정 필터를 설계 및 적용한다. 제안된 방법의 적용을 위해 지터 노이즈와 초점 커브는 가우시안 함수로써 모델링한다. 실험 결과들을 통해 제안된 방법의 효율성을 증명한다.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제55권2호
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• pp.89-97
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using learning mechanism-fuzzy neural network(LM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_{d}$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using LM-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using LM-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the LM-FNN and ANN controller.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2011년도 전력전자학술대회
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• pp.103-104
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• 2011

This paper suggests a new starting and stopping method appropriate for the sensorless PMSM drive with air bearings. The proposed method based on the sensorless control algorithm of PMSM uses additional d-axis current control to cope with the limitation of the adopted back-emf based sensorless algorithm in the low speed region. The experimental results show that the proposed method drives appropriately the PMSM with air bearings.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권4호
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• pp.184-191
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• 2001

This paper proposes a prefilter type velocity compensating control system using modified chaotic neural networks for the trajectory control of robotic manipulator. Since the structure of modified chaotic neural networks(MCNN) and neurons have highly nonlinear dynamic characteristics, MCNN can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis robot manipulator is designed by MCNN. The MCNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on-line learning and the performance is excellent. The MCNN controller showed much better control performance and shorter calculation time compared to the RNN controller, Another advantage of the proposed controller could by attached to conventional robot controller without hardware changes.

• 한국지반신소재학회논문집
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• 제20권4호
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• pp.19-32
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• 2021

본 연구에서는 심층혼합처리공법에 관하여 저자들에 의해 수행된 국내/외 설계, 시공 및 품질관리에 대한 평가와 고찰을 수행하였고, 추후 DCM 공법의 발전을 위한 개선 사항들을 제시하였다. 본 연구 결과, 실내배합실험 시 강도에 대한 단면적 보정이 필요하고, 외삽법 적용 시 실제와 다른 결과가 도출될 수 있으므로 주의가 요구됨을 알 수 있었다. 설계 시 개량율과 개량형식 등을 모두 고려하여 적용 가능한 설계법을 선정해야 하며, 안전율이 적용된 허용압축강도는 안정성 검토를 위한 기준치를 의미하는 것이지 설계 지반정수가 아님을 확인하였다. 응력분담비의 경우 관행적인 값을 적용하기 보다는 설계 조건을 반영한 실험 및 이론적 응력분담비를 산정해야 경제적인 설계를 수행할 수 있었다. 시공 시 선천공이 예상되는 경우 증가된 함수비가 원지반 대비 크지 않은 경우 함수비 증가를 고려하지 못한 결과를 사용하여도 큰 문제가 발생하지 않는 경우도 있었다. 또한, 개량길이 대비 선단처리 길이의 비율이 높은 경우 시공 시 단위길이당 설계 시멘트량이 적게 주입될 수 있음을 확인하였다. 품질관리 시 개량체 코어링은 1축 개량체는 D/4~2D/4, 다축 개량체는 D/4 지점이 최적인 것으로 평가되었다. 품질관리를 위한 항목으로 개량체의 일축압축강도와 더불어 TCR을 고려하는 기준이 국내 실정에 더 적합할 것으로 판단된다.

• 전력전자학회논문지
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• 제7권6호
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• pp.524-530
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• 2002

일상 생활에서 반사적인 자세 조절은 정전기관, 시각, 고유수용체 등의 감수체에 의한 구심성 신호가 정전 신경핵에 전달되어 안구운동이나 골격근의 수축을 유발하여 이루어진다. 자세조절기능의 부조화는 오심, 구토, 현기증 등을 초래하여 삶의 의욕을 상실하게 만든다. 본 연구의 목적은 정전기관의 반규관과 이석기관을 선별적으로 자극하기 위한 탈수직축 회전자극 시스템과 수평, 수직, 3D 환경에서 시각자극을 할 수 있는 시운동자극시스템을 개발하여 인간의 자세조절 기능을 평가 하는데 있다. 탈수직축 회전자극 시스템은 편안한 의자와 DC 서보모터로 구동되는 기울임 테이블로 구성되고 PMSM에 의해 제어된다. 그리고 속도 궤환 루프와 위치 궤환 루프를 포함하는 이중 피드백 루프가 서보 제어되는 회전자극시스템에 적용된다. HMD를 이용하여 수평, 수직, 3D 시각자극패턴을 구현 하였고 OKN 자극을 위한 무선시스템과 전기안진 기록계를 이용하여 안구운동을 기록하였다. 이득, 위상, 대칭성은 정전 자극과 시각 자극에 의해 유발되는 안구운동의 분석으로부터 얻어진다.

• Journal of Electrical Engineering and Technology
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• 제13권6호
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• pp.2354-2363
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• 2018

This paper proposed a novel double closed control strategy for single-phase voltage source pulse width modulation (PWM) rectifier based on active disturbance rejection control (ADRC) and dq current decoupling control. First, the mathematical model of the single-phase PWM rectifier in the d-q axis synchronous rotating reference frame is established by constructing a virtual component using a second-order generalized integrator (SOGI). Then, the mathematical model is simplified according to the active power conservation, and the first-order equation of single-phase PWM rectifier voltage outer loop is acquired. A linear auto-disturbance rejection controller is used to design the voltage outer loop according to the first-order equation. Finally, the proposed control strategy and the traditional PI control are compared and verified by simulation and physical experiments. Both simulation and experimental results confirm that the proposed control strategy has excellent dynamic performance and strong rejection ability to disturbances.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.566-569
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• 2005

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using artificial intelligent(AI) controller. The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AI controller. This paper is proposed speed control of IPMSM using learning mechanism fuzzy neural network(LM-FNN) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also. this paper is proposed the experimental results to verify the effectiveness of AI controller.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2006년도 춘계학술대회 논문집
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.