• Title/Summary/Keyword: motors

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High performance velocity and position controller for spindle motor (스핀들용 유도 전동기 고성능 속도 및 위치 제어기)

  • 임충혁;유준혁;김동일;김성권
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.648-651
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    • 1996
  • Samsung Electronics has developed high performance velocity and position controller for induction motors, and succeeded in mass production for the first time in Korea. Dynamic performance and final control accuracy of the controller are equivalent to those of AC servo motor controller. At present, we adopted the controller as spindle motor drive for Samsung CNC systems, and expect its wide use in industry as general purpose velocity and position controller for induction motor.

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Development of driver for BLDC motor system and precise repetitive control (BLDC 모터의 구동장치 개발 및 정밀 반복제어)

  • 강병철;이충환;김상봉
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1257-1260
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    • 1996
  • This paper describes a fully digitalized driver for BLDC motors and the driver is realized by a single chip microprocessor. The speed change can be done by using the signal obtained from the position detecting sensor and adjusting the pulse width at the input channel of power module. In order to verify the effectiveness, an repetitive control method is adopted in the speed control tracking a periodic reference change in the BLDC motor system. The experimental results are shown for the reference tracking accurately according to the design parameter variation in the repetitive controller design.

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Time-optimal control for motors via neural networks (신경회로망을 이용한 모터의 시간최적 제어)

  • 최원수;윤중선
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.1169-1172
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    • 1996
  • A time-optimal control law for quick, strongly nonlinear systems has been developed and demonstrated. This procedure involves the utilization of neural networks as state feedback controllers that learn the time-optimal control actions by means of an iterative minimization of both the final time and the final state error for the known and unknown systems with constrained inputs and/or states. The nature of neural networks as a parallel processor would circumvent the problem of "curse of dimensionality". The control law has been demonstrated for a velocity input type motor identified by a genetic algorithm called GENOCOP.

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The Speed and Position Sensorless Control of PMSM using the Sliding Mode Observer with the Estimator of Stator Resistance (고정자 저항 추정기를 갖는 슬라이딩 모드 관측기를 이용한 영구자석 동기전동기의 속도 및 위치 센서리스제어)

  • 한윤석;최정수;김영석
    • Proceedings of the KIPE Conference
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    • 1998.11a
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    • pp.23-27
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    • 1998
  • This paper presents a new speed and position sensorless control method of permanent magnet synchronous motors based on the sliding mode observer. The sliding mode observer structure and its design method are discussed. Also, Lyapunov functions ar chosen for determining the adaptive law for the speed and the stator resistance estimator. The effectiveness of the proposed observer is confirmed by the computer simulation.

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Speed Sensorless Direct Vector Control of Induction Motors Considering Iron-Loss (철손을 고려한 유도기의 센서리스 직접 베터 제어)

  • 위성돈;신명호;현동석
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.501-504
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    • 1999
  • 과거 벡터 제어의 모델링에 있어 무시되어온 철손의 영향이 최근 여러 논문들에서 연구되어졌으며, 이의 영향이 적지 않음이 밝혀졌다. 본 논문은 속도 센서리스에서의 철손으로 인한 영향을 보상, 직접 회전자 자속 제어와 직접 고정자 자속 제어에 적용하였다. 또한 센서리스 제어에서의 철손의 영향과 그 보상 방법을 보여주며, 시뮬레이션을 통해 이러한 제안의 타당성을 보인다.

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Sensorless Vector of High Speed Motor Drives based on Neural Network Controllers using Kalman Filter Learning Algorithm (칼만필터 학습 신경회로망을 이용한 고속 유도전동기의 센서리스 제어)

  • 이병순;김윤호
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.518-521
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    • 1999
  • This paper describes high speed squirrel cage induction motor drives without speed sensors using neural network based on Kalman filter Learning. High speed motors are receiving inverasing attentions in various applications, because of advantages of high speed, small size and light weight with same power level. Larning rate by Kalman filtering is time varying, convergence time fast, effect of initial weight between neurons is small.

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Sensorless speed control of a Switched Reluctance Motor using intelligent controller (지능 제어기를 이용한 SRM 센서리스 속도제어에 관한 연구)

  • 최재동;김민태;오성업;황영성;김영록;성세진
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.179-183
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    • 1999
  • This paper describes a new method for indirect sensing of the rotor position in switched reluctance motors using fuzzy logic algorithm. Through a novel fuzzy algorithm, the complete SRM magnetizing characterization is first constructed, and then used to estimate the rotor position. And also, the optimized phase is selected by phase selector. To demonstrate the promise of this approach, the proposed rotor position estimation algorithm is simulated for variable speed range.

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Switching Angle Selection for Maximum Torque in Toroidal SRM (Toroidal SRM의 최대토크 스위칭각 선정)

  • 차현록;김현덕;김광헌;임영철;최유영;최강식;전흥기
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.135-138
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    • 1999
  • This paper analysis magnetic circuit of toroida SRM and simulate optimal switching angle. In this troidal SRM, two of three phase are energized at an arbitrary instance while it is with only one phase in case of typical SRM. It has many advantages in the size of machine and power efficiency. Not only typically Known topologies witched reluctance motors such as asymmetric converter but full bridge converter are safe to employ

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Torque Control Scheme of Switched Reluctance Motor using Neural Network (신경회로망을 이용한 SRM의 토오크 제어)

  • 정연석;이장선;김윤호
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.171-174
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    • 1999
  • The torque of SRM is developed by phase currents and inductance variation. Phase currents and inductance variation. Phase current is often the controlled variable in electrical motor drives, so it seems natural to use closed loop current controllers. However, the highly nonlinear nature of switched reluctance motors makes optimisation of closed loop current controlled difficult because of saturation effect in magnetic circuit. Therefore, torque generation region is nonlinearly varied according to phase current and rotor position. This paper describes the torque control scheme with neural network that can control varied with load torque. The torque control is simulated by PSIM.

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PMSM Angle Detection Based on the Edge Field Measurements by Hall Sensors

  • Kim, Jae-Uk;Jung, Sung-Yoon;Nam, Kwang-Hee
    • Journal of Power Electronics
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    • v.10 no.3
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    • pp.300-305
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    • 2010
  • This paper presents a two Hall sensor method for rotor angle detection in permanent magnet synchronous motors (PMSM). To minimize the implementation complexity, the system is designed to measure the edge field of permanent magnet pieces. However, there are nonlinearities in the measured values of the edge field. In this work, an angle correction algorithm is proposed, and the improvements in accuracy are verified through experiments. Finally, a field orientation controller is constructed with the proposed angle detection algorithm.