• Title/Summary/Keyword: Motor control center

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Design of Driver and Controller for micro Brushless DC Motor (초소형 Brushless DC Motor의 구동 및 제어기 설계)

  • Lee, Jong-Bae;Jeong, In-Sung;Lim, Joon-Hong
    • Proceedings of the KIEE Conference
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    • 2002.11c
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    • pp.329-332
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    • 2002
  • Recently, most machineries have been small size and mobile type. Then the motors used in this field are developed in micro size such as about 2mm in diameter. The structure of this motor is similar to a general brushless DC motor but because of small sige there is no position sensor such as hall sensor. In this paper, we propose synchronous driving and control method for micro brushless DC motor without position sensor. We design and manufacture this controller and perform experiment to show the effectiveness of the proposed method.

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Fuzzy-Neuro Controller for Speed of Slip Energy Recovery and Active Power Filter Compensator

  • Tunyasrirut, S.;Ngamwiwit, J.;Furuya, T.;Yamamoto, Y.
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.480-480
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    • 2000
  • In this paper, we proposed a fuzzy-neuro controller to control the speed of wound rotor induction motor with slip energy recovery. The speed is limited at some range of sub-synchronous speed of the rotating magnetic field. Control speed by adjusting resistance value in the rotor circuit that occurs the efficiency of power are reduced, because of the slip energy is lost when it passes through the rotor resistance. The control system is designed to maintain efficiency of motor. Recently, the emergence of artificial neural networks has made it conductive to integrate fuzzy controllers and neural models for the development of fuzzy control systems, Fuzzy-neuro controller has been designed by integrating two neural network models with a basic fuzzy logic controller. Using the back propagation algorithm, the first neural network is trained as a plant emulator and the second neural network is used as a compensator for the basic fuzzy controller to improve its performance on-line. The function of the neural network plant emulator is to provide the correct error signal at the output of the neural fuzzy compensator without the need for any mathematical modeling of the plant. The difficulty of fine-tuning the scale factors and formulating the correct control rules in a basic fuzzy controller may be reduced using the proposed scheme. The scheme is applied to the control speed of a wound rotor induction motor process. The control system is designed to maintain efficiency of motor and compensate power factor of system. That is: the proposed controller gives the controlled system by keeping the speed constant and the good transient response without overshoot can be obtained.

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Low Parameter Sensitivity Deadbeat Direct Torque Control for Surface Mounted Permanent Magnet Synchronous Motors

  • Zhang, Xiao-Guang;Wang, Ke-Qin;Hou, Ben-Shuai
    • Journal of Power Electronics
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    • v.17 no.5
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    • pp.1211-1222
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    • 2017
  • In order to decrease the parameter sensitivity of deadbeat direct torque control (DB-DTC), an improved deadbeat direct torque control method for surface mounted permanent-magnet synchronous motor (SPMSM) drives is proposed. First, the track errors of the stator flux and torque that are caused by model parameter mismatch are analyzed. Then a sliding mode observer is designed, which is able to predict the d-q axis currents of the next control period for one-step delay compensation, and to simultaneously estimate the model parameter disturbance. The estimated disturbance of this observer is used to estimate the stator resistance offline. Then the estimated resistance is required to update the designed sliding-mode observer, which can be used to estimate the inductance and permanent-magnetic flux linkage online. In addition, the flux and torque estimation of the next control period, which is unaffected by the model parameter disturbance, is achieved by using predictive d-q axis currents and estimated parameters. Hence, a low parameter sensitivity DB-DTC method is developed. Simulation and experimental results show the validity of the proposed direct control method.

A Novel Predictive Current Control of Induction Motor Using Resonant DC Link Inverter (공진형 직류 링크단을 이용한 유도전동기의 예측형 전류 제어)

  • Oh, In-Hwan;Moon, Gun-Woo;Kim, Sung-Kwun;Youn, Myung-Joong
    • Proceedings of the KIEE Conference
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    • 1996.07a
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    • pp.567-570
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    • 1996
  • A predictive current control technique for an induction motor employing a resonant DC link inverter is proposed to overcome the disadvantage of the current regulated delta modulation(CRDM) which was employed to control the resonant DC link inverter. The discrete model of an induction motor and estimation of back EMF are investigated and a novel predictive current control technique is newly developed based on this discrete model and estimated back EMF. Using the proposed control technique, the minimized current ripple with reduced offset can be obtained. The usefulness of the proposed technique is verified through the computer simulation.

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A Study on the Dynamic Analysis and Control Algorithm for a Motor Driven Power Steering System

  • Yun, Seokchan;Han, Changsoo;Wuh, Durkhyun
    • Journal of Mechanical Science and Technology
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    • v.16 no.2
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    • pp.155-164
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    • 2002
  • The power steering system for vehicles is becoming essential for supporting the steering efforts of the drivers, especially for the parking lot maneuver Although hydraulic power steering has been widely used for years, its efficiency is not high enough. The problems associated with a hydraulic howe. steering system can be solved by a motor driven power steering (MDPS) system. In this study, a dynamic model and a control algorithm for the ball screw type of MDPS system have been derived and analyzed by using the method of discrete modeling technology. To improve steering feel and power steering characteristics, two derivative gains are added to the conventional power boosting control algorithm. Through simulations, the effects of the control gain on the steering angle gain were verified in the frequency domain. The steering returnability and steering torque phase lag in on-center handling test were also evaluated in the time domain.

A Study on the Control Algorithm for a Ball Screw Type of Motor Driven Power Steering System (Ball screw형 전동식 동력 조향 장치의 제어에 관한 연구)

  • 윤석찬;왕영용;한창수
    • Transactions of the Korean Society of Automotive Engineers
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    • v.8 no.1
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    • pp.124-134
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    • 2000
  • The power wteering system for automobiles is becoming core popular for supporting steering efforts of the drivers, especially for a parking lot maneuver. Though hydraulic power steering has been widely used for a long time, the efficiency of that is not high enough. The motor driven power steering system can solve the problems associated with the hydraulic power steering system. In this study, dynamic model and control algorithm of the ball screw type of MDPS systenem have been derived and analysed by using the method of discrete modeling technology. To improve steering feel and power steering characteristics, the additional scheme is proposed to the conventional power boosting control algorithm. Through simulations, control gain effects to the steering angle gain in the frequency domain were verified. The steering returnability and steering torque phase lag in on-center handing test were performed also.

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High Performance Velocity and Position Controller for Induction Motors (유도 전동기 고성능 속도 및 위치 제어기)

  • Yim, Chung-Hyuk;Kim, Chang-Hwan;Kim, Dong-Il;Kim, Sung-Kwon;Sul, Seung-Ki
    • Proceedings of the KIEE Conference
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    • 1996.07a
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    • pp.281-284
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    • 1996
  • Samsung Electronics has developed high performance velocity and position controllers 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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Design and Fabrication of Novel Linear Ultrasonic Motor (선형 초음파 모터 설계 및 제작)

  • Lee, Dong-Kyun;Han, Deuk-Young;Choi, Ji-Won;Kim, Hyun-Jai;Yoon, Seok-Jin
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2003.07b
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    • pp.776-778
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    • 2003
  • In the paper, the novel linear ultrasonic motor for precision position control was designed and fabricated. It was composed of two piezoelectric actuators with longitudinal ultrasonic fluctuations and shaking beam. When two AC electric fields ($Usin{\omega}t$, $Ucos{\omega}t$) were applied in two piezoelectric actuators respectively, the middle part of shaking beam had an elliptical trajectory. According to experimental results, good symmetrical characteristic of two piezoelectric actuators were obtained.

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Identification of Parameters for Induction Motor at Standstill (완전 정지형 방식에 의한 유도 전동기 파라미터 오토튜닝)

  • Kim J.H.;Hong C.O.;Kwon B.H.;Lim K.Y.
    • Proceedings of the KIPE Conference
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    • 2003.07b
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    • pp.900-903
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    • 2003
  • An identification method of induction motor parameters such as rotor time constant and mutual inductance at standstill condition is discussed assuming that stator resistance and leakage has already been obtained applying two different DC voltage and single phase voltage to the induction motor, respectively. This proposed scheme is implemented by means of Model Reference Adaptive Control (MRAC) technique, which uses a rotor flux equation in voltage model as a reference model and one in current model and is demonstrated through experiment.

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A Control Method of DC Servo Motor Using a Multi-Layered Neural Network (다층 신경회로망을 이용한 DC Servo Motor 제어방법)

  • Kim, S.W.;Kim, J.S.;Ryou, J.S.;Lee, Y.J.
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.855-858
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    • 1995
  • A neural network has very simple construction (input, output and connection weight) and then it can be robusted against some disturbance. In this paper, we proposed a neuro-controller using a Multi-Layered neural network which is combined with PD controller. The proposed neuro-controller is learned by backpropagation learning rule with momentum and neuro-controller adjusts connection weight in neural network to make approximate dynamic model of DC Servo motor. Computer Simulation results show that the proposed neuro-controller's performance is better than that of origianl PD controller.

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