• Proceedings of the KIPE Conference
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• 2007.11a
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• pp.4-6
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• 2007

본 논문에서는 안티 와인드업(Anti Windup) 제어 성분을 이용하는 약자속(Flux Weakening) 제어기에 있어, 약자속제어기의 제정수 변화가 전체 제어 성능에 미치는 영향에 관하여 분석하고, 그 결과에 근거하여 제정수 변화의 영향을 줄일 수 있는 방법을 제시하였다. 약자속 제어기는 제정수의 변동에 비교적 강인하나 전류제어기가 제정수의 영향을 받아 성능이 저하(Degradation) 될 수 있다. 이러한 성능의 저하는 가상의 능동 저항 성분을 전류 제어기에 도입함으로써 완화될 수 있다.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.119-123
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• 2007

This paper investigates a speed sensorless control of induction motor. The control strategy is based on MRAS(Model Reference Adaptive System) using load-torque observer as a reference model for flux estimation. The speed response of conventional MRAS controller characteristics is affected by variations of load torque disturbance. In the proposed system, the speed control characteristics using a load-torque observer control isn't affected by a load torque disturbance. Control algorithm that propose whole system through MATLAB SIMULINK because do modelling simulation result are presented to prove the effectiveness of the adaptive sliding mode controller for the drive variable load of induction motor. Therefore we hope to be extended in industrial application.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.1
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• pp.1-10
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• 2011

This paper proposes a new fuzzy load torque observer and a fuzzy speed regulator to guarantee a robust speed control of a permanent magnet synchronous motor (PMSM). Also, the LMI conditions are given for the existence of the fuzzy load torque observer and fuzzy speed controller, and the gains of the observer and controller are calculated. The stability of the proposed control system is analytically proven. To validate the effectiveness of the proposed observer-based fuzzy speed controller, the simulation and experimental results are presented. Finally, it is definitely demonstrated that the proposed control algorithm can be used to accurately control the speed of a PM synchronous motor.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.26 no.1
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• pp.76-80
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• 1990

DC-servomotor acts an important role in robots and manipulatirs. But the precise control of DC-motor is difficult by a using usual linear controller because of the nonlinear characteristics of DC-motor. This study suggests the use of fuzzy controller in the control of DC-servomotor speed. The fuzzy controller is designed from a fuzzy model which can represent nonlinear systems very well. Hence the fuzzy controller is very useful in the control of nonlinear systems such as DC-motor. We construct a fuzzy model of DC-servomotor, design a fuzzy controller from the fuzzy model, and compare that with a linear controller. When we use the fuzzy controller, the static ripples are reduced and the rise time is required 20% less than in using a linear controller.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.212-218
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• 2007

This paper presents a implementation of speed sensorless vector control of induction motor using MATLAB/SIMULINK and dSPACE DS1104. Proposed flux estimation algorithm, which utilize the combination of the voltage model based on stator equivalent model and the current model based on rotor equivalent model, enables stable estimation of rotor flux. Proposed rotor speed estimation algorithm utilizes the estimated flux. And the estimated rotor speed is used to speed control of induction motor. Overall system consists of speed controller, current controller, and flux controller using the most general PI controller. Speed sensorless vector control algorithm is implemented as block diagrams using MATLAB/SIMULINK. And realtime control is performed by dSPACE DS1104 control board and Real-Time-Interface(RTI).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network 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 results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.71-74
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• 2002

본 논문에서는 유전알고리즘(GA)을 이용한 PID계수 자동조정기법에 관한 DC 서보 모터 속도 제어기 설계를 목적으로 한다. DC 서보 모터는 수많은 제어용 기계나 로봇 등의 응용분야에 사용되고 있고 이러한 분야에서 제어기 파라미터들의 선택이 사용자의 전문적인 지식을 요구하게 된다. 따라서 일반적인 공정 기술자들은 시행착오에 의해 제어기 파라미터들을 계속적으로 반복 조절해 나가야 한다. 이와 같이 동적 시스템의 변화나 외란에 대하여 파라미터 계수를 자동 조정해야 할 경우 유전알고리즘을 사용함으로써 보다 정밀하고 최적화된 파라미터 계수값을 추종함에 따라 그 성능을 높일 수 있다. 본 논문에서는 DC 모터의 동특성을 분석하여 얻은 동특성 모델링으로부터 응답 특성이 빠르고 속도 정밀도가 향상된 구동제어가 가능한 제어기를 설계하고 이를 PID제어기와 비교 평가하였다.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.6
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• pp.531-536
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• 2002

This paper investigates the problem of the speed controller of conventional speed sensorless stator flux-oriented(SFO) induction motor drive, and proposes a robust speed controller to solve the conventional problem. In the proposed method, a robust speed controller for speed sensorless SFO system Is designed by taking advantage of disturbance torque observer and using feedforward.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1117-1119
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• 2003

기존의 사다리꼴형 브러시리스 직류 전동기(BLDCM)의 센서리스 제어는 전류전환 시점을 알기 위하여 홀 센서 대신 단자 전압과 중성점 전압을 이용한다. 하지만, 속도 제어를 위해서는 엔코더나 레졸바와 같은 센서를 사용해야한다. 2극기 BLDC 모터의 경우 단자전압을 이용한 위치정보는 모터 한 회전 당 12번의 신호가 출력된다. 엔코더 혹은 레졸바를 제거하고, 이 신호를 이용하여 속도 정보를 만들 경우, 속도를 만들기 위한 위치 정보의 펄스 간격이 넓게 되어 순시 속도를 만들지 못하게 된다. 이로 인하여 실제 속도의 변화를 민감하게 추정하지 못하게 된다. 따라서 이렇게 만들어진 속도 정보는 실제 시스템에서 사용할 수 없게 된다. 이러한 문제를 해결하려고 본 논문에서는 순시 속도 관측기를 사용한다 단자전압과 중성점 전압에 의한 위치정보를 가지고 순시 속도 관측기를 속도 제어 주기보다 빠르게 갱신함으로써 순시 속도를 예측한다. 또한 이 순시 속도는 속도 제어기로 피드백 되어 속도 센서리스를 실현한다. 이에 대한 타당성은 시뮬레이션을 통해 검증한다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.157-165
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• 2002

This paper presents the implementation of the speed control system for 3 phase induction motor using PD controller and neural networks. The PD controller is used to control the motor and to train neural networks at the first time. And neural networks are widely used as controllers because of a nonlinear mapping capability, we used feedforward neural networks(FNN) in order to simply design the speed control system of the 3 phase induction motor. Neural networks are tuned online using the speed reference, actual speed measured from an encoder and control input current to motor. PD controller and neural networks are applied to the speed control system for 3 phase induction motor, are compared with PI controller through computer simulation and experiment respectively. The results are illustrated that the output of the PD controller is decreased and feedforward neural networks act main controller, and the proposed hybrid controllers show better performance than the PI controller in abrupt load variation and the precise control is possible because the steady state error can be minimized by training neural networks.