• Title/Summary/Keyword: Vector control algorithm

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A Control Algorithm of Linear Induction Motor based on Indirect Vector Control (간접 벡터 제어에 근거한 선형유도전동기의 제어 알고리즘)

  • Lee, Jae-Hyun;Jeon, Mi-Rim;Mok, Hyung-Soo;Lee, Jin-Woo;Kim, Sang-Hoon;Kim, Chul-Ho;Chung, Eun-Sung
    • Proceedings of the KSR Conference
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    • 2008.11b
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    • pp.302-309
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    • 2008
  • This paper presents a vector control of Linear Induction Motor base on a slip frequency control. And a linear induction motor modeling included the end effect using circuit and equation method is also proposed. We demonstrated through simulation the improvements achieved by the proposed scheme.

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A Study of Control Algorithm for Propulsion System (열차 추진제어장치의 알고리즘에 관한 연구)

  • Choi, Jae-Ho;Kim, Hyung-Chul
    • Journal of the Korean Society for Railway
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    • v.10 no.1 s.38
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    • pp.51-56
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    • 2007
  • In this paper, control schemes are developed for a propulsion system(Converter/Inverter) in electrical train. A robust controller for PWM converter is proposed. The converter controller consists of a PI controller for DC output voltage and a current controller using error-space approach for maintaining the sinusoidal current waveform and unity power factor. This proposed method is based on characteristic ratio assignment(CRA) method which has the advantage to design the optimal gain to meet the referenced response and overshoot within the limit range. Inverter system is controlled by vector control and slip frequency control. At low speed region, vector control scheme is applied to control instantaneous torque and slip frequency control is performed under overmodulation region and one pulse mode. Because output voltage of converter contains harmonics ripple at twice input ac line frequency, control scheme is developed to reduce the pulsating torque current. The performance of propulsion system will be verified by simulation and prototype experimental results.

Sensorless Vector Control of a Wound Induction Motor Using MRAS with On-Line Stator Resistance Tuning

  • Lee Jae-Hak;Kim Yoon-Ho;Lee Houng-Gyun;Woo Hyuk-Jae
    • Proceedings of the KIPE Conference
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    • 2001.10a
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    • pp.462-465
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    • 2001
  • The wound induction motor can provide high starting torque and reduced starting current simultaneously by inserting large scale resistor. And this technique is one of the well known methods among the induction motor starting methods and generally used for heavy load starting such as Crain and Cement factories. The conventional PI controller has been widely used in industrial application due to the simple control algorithm and in general, PI controller is used for control of current, torque, position, and speed for the wound induction motor drive system. However, the system may result in poor performance since sensors have to be used, which in turn is limited by the environmental condition. Recently, to overcome these problems, many sensorless vector control methods for the wound induction motor have been studied. This paper presents MRAS method with on-line stator resistance tuning for sensorless vector control of the wound induction motor drive. In conventional MRAS method, in low frequency, stator resistance variation can result in poor performance. Therefore, to overcome several shortages of the conventional MRAS caused by parameter variation and enhance robustness of the sensor less vector control, this paper investigates a MRAS method with on-line stator resistance tuning for sensorless vector control of the wound induction motor. The validity and effectiveness of the proposed method is verified through digital simulation.

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Sensorless Vector Control of Induction Motor Using Neural Networks (신경망을 이용한 유도전동기 센서리스 벡터제어)

  • Park, Seong-Wook;Choi, Jong-Woo;Kim, Heung-Geun;Seo, Bo-Hyeok
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.53 no.4
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    • pp.195-200
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    • 2004
  • Many kinds of speed sensorless control system of induction motor had been developed. But it is difficult to implement at the real system because of complex algorithm and equations. This paper investigates a novel speed sensorless control of induction motor using neural networks. The proposed control strategy is based on neural networks using stator current and output of neural model based on state observer. The errors between the stator current and the output of neural model are back-propagated to adjust the rotor speed, so that adaptive state variable will coincide with the desired state variable. This algorithm may overcome several shortages of conventional model, such as integrator problems, small EMF at low speed and relatively large sensitivity of stator resistance variation. Also, this paper presents a newly developed optimal equation about the momentum constant and the learning rate. The proposed algorithms are verified through simulation.

An Enhanced Finite-Settling-Step Direct Torque and Flux Control (FSS-DTFC) for IPMSM Drives

  • Kim, Sehwan;Seok, Jul-Ki
    • Journal of Power Electronics
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    • v.16 no.4
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    • pp.1367-1374
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    • 2016
  • This paper presents a discrete-time version of voltage and current limited operation using an enhanced direct torque and flux control method for interior permanent magnet synchronous motor (IPMSM) drives. A command voltage vector for airgap torque and stator flux regulation can be uniquely determined by the finite-settling-step direct torque and flux control (FSS-DTFC) algorithm under physical constraints. The proposed command voltage vector trajectories can be developed to achieve the maximum inverter voltage utilization for the discrete-time current limit (DTCL)-based FSS-DTFC. The algorithm can produce adequate results over a number of the potential secondary upsets found in the steady-state current limit (SSCL)-based DTFC. The fast changes in the torque and stator flux linkage improve the dynamic responses significantly over a wide constant-power operating region. The control strategy was evaluated on a 900W IPMSM in both simulations and experiments.

Development of Continuous Process Control System Using Torque Controlled Vector Inverter (벡터 인버터의 토크 제어를 이용한 연속공정 제어 시스템 개발)

  • Byun, S.H.;Cheong, J.Y.;Hong, C.O.;Kim, K.S.
    • Proceedings of the KIPE Conference
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    • 2010.07a
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    • pp.314-315
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    • 2010
  • This paper presents the design and development of Web control algorithm of continuous process control system using torque controlled vector inverter. Web algorithm used tension control with the tension sensor, and it is to calculate diameter of motor speed with maintain Web tension. The performance of Web control in this paper is verified by experiment.

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The speed control of induction motor using neural networks (신경회로망을 이용한 유도전동기 속도제어)

  • 김세찬;원충연
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.45 no.1
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    • pp.42-53
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    • 1996
  • The paper presents a speed control system of vector controlled induct- ion motor using neural networks. The main feature of proposed speed control system is a Neural Network Controller(NNC) which supplies torque current to induction motor and Neural Network Emulator(NNE) which captures the forward dynamics of induction motor. A back propagation training algorithm is employed to train the NNE and NNC. In order to determine the NNC output error, plant(induction motor) output error can be back propagated through the NNE. The NNC and NNE for speed control of vector controlled induction motor is carried out by TMS320C30 DSP and IGBT current regulated PWM inverter. Through computer simulation and experimental results, it is verified that proposed speed control system is robust to the load variation. (author). refs., figs.

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A Study on the Pseudoinverse Kinematic Motion Control of 6-Axis Arc Welding Robot (6축 아크 용접 로보트의 의사 역기구학적 동작 제어에 관한 연구)

  • Choi, Jin-Seob;Kim, Dong-Won;Yang, Sung-Mo
    • Journal of the Korean Society for Precision Engineering
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    • v.10 no.2
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    • pp.170-177
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    • 1993
  • In robotic arc welding, the roll (rotation) of the torch about its direction vector does not have any effect on the welding operation. Thus we could use this redundant degree of greedom for the motion control of the robot manipulator. This paper presents an algorithm for the pseudo- inverse kinematic motion control of the 6-axis robot, which utilizes the above mentioned redunancy. The prototype welding operation and the tool path are also graphically simulated. Since the proposed algorithm requires only the position and normal vector of the weldine as an input data, it is useful for the CAD-based off-line programming of the arc welding robot. In addition, it also has the advantages of the redundant manipulator motion control, like singularity avoidance and collision free motion planning, when compared with the other motion control method based on the direct inverse kinematics.

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Vector Control of an Induction Motor with Forced Commutated Cycloconverter (강제전류 싸이크로콘버터에 의한 유도전동기 벡터제어)

  • Gi Taek Kim
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.9
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    • pp.1239-1246
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    • 1995
  • A forced commutated cycloconverter (FCC) is a direct ac-ac converter capable of providing simultaneous voltage and frequency transformations. In this paper, vector control of an induction motor controlling stator current with forced commutated cycloconverter is presented. The advantage of current control is that the stator dynamics are eliminated and high performance vector control can be achieved. A novel modulation method based on dq transformation techniques is presented. Proposed modulation strategy generates the low frequency modulation function by the instantaneous value of the desired output voltages not by the steady state values of output magnitude and output frequency. PI control and predictive control algorithm for current control are applied, and the validity of proposed method is confirmed through digital simulations. Simulation results of step response and torque distubance and current control are presented.

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Fingerprint Classification and Identification Using Wavelet Transform and Correlation (웨이블릿변환과 상관관계를 이용한 지문의 분류 및 인식)

  • 이석원;남부희
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.5
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    • pp.390-395
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    • 2000
  • We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.

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