• Proceedings of the KIPE Conference
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• 2004.07a
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• pp.42-45
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• 2004

This paper is proposed an adaptive fuzzy controller of induction motor drive. The adaptive fuzzy controller approach for an estimate of the rotor time constant which is used to adjust the estimate of the slip angular speed. An estimate of the rotor time constant was obtained using an model reference adaptive system(MRAS) in a fuzzy control scheme. The rotor time constant was estimated by utilizing the rotor nut estimates. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Journal of Power Electronics
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• v.15 no.3
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• pp.730-740
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• 2015

This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1165-1168
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.213-216
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• 2002

This paper describes a new approach to estimate induction motor speed from terminal voltages and currents for speed-sensorless vector control. This algorithm is based on Model Reference Adaptive System(MRAS). The proposed technique is simple and robust to the variation of motor parameters. Specially, this algorithm is not affected by the variation of stator resistance and it does not require any pure integration at all. The validity of this new approach is proved by simulations.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.434-436
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• 1997

본 연구에서는 저속에서 발생하는 측정잡음에 대한 문제를 불규칙 확률시스템으로 고려하여 Kalman 필터를 관측자로서 사용하고 고속에서뿐만 아니라 저속에서의 위치와 속도 추정성능을 향상시키고자 한다. Kalman 필터는 확률적 외란을 포함하고 있는 동적시스템에 적용되는 최적상태 추정자이다. 또한 이 Kalman 필터는 외란을 가지는 이산형 실시간 동적 처리 시스템에서 최적의 미지 상태를 추정하기 위해 선형, 불편향, 그리고 최소 오차분산 회귀형 알고리즘을 제공한다. 또한, MRAS(Model Reference Adaptive System) 방법을 이용하여 모터와 부하에 대응되는 기계적 시정수를 동정한다. 이 방법은 기계적인 시정수가 알려지지 않은 시스템에 적용하여 위치와 속도의 추정을 가능하게 하기 위해서이다. 더욱이 동정의 결과를 이용하여 Kalman 필터 알고리즘에 적용한다.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.6
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• pp.594-601
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• 2011

In this paper, a new current controller with the compensation of an unbalance and distorted grid voltages has been proposed. Generally, in the three-phase power system, single phase or nonlinear loads can be connected with the 3 phase linear load simultaneously on the same point of common coupling. Therefore, The source voltage unbalance and distortion problem can be occurred. Under these unbalance and distorted grid voltage conditions, the input current of 3 phase PWM rectifiers also have unbalance and distortion. In this paper, a current controller with the simple Model Reference Adaptive System based unbalance and distorted voltages observer is proposed to get a sinusoidal input current. The performance of the proposed algorithm is verified through the simulation and the experiment.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.1123-1133
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• 2012

This study configuration Vector Control System which is stable and has outstanding Dynamic Characteristics in Very Low Speed Region and Low Speed Region, and proposes Instantaneous Speed Observer and Very Low Speed Control method and vector control system of the speed estimation a using Reduced-Dimensional State Observer. The Observer proposed in this system, by appling Reduced-Dimensional State Observer to Load-Torque estimation and using for speed estimation, implements system composition simply and is capable of accurate Instantaneous Speed estimation in Very Low Speed Region. Also, this study reduces influence by System Noise and suggests an induction motor speed control system which is effective in Load Disturbance, modeling error, estimation noise and so on without changing pole of an Observer.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.5
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• pp.22-33
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• 2011

An induction motor operated with a conventional direct self controller(DSC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic controller(FLC) is used in conjection with DSC to minimize these problems. A FLC chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determinated by observing the vector diagram of flux and currents. This paper proposes hybrid fuzzy controller for direct torque control(DTC) of induction motor drives. The speed controller is based on adaptive fuzzy learning controller(AFLC), which provide high dynamics performances both in transient and steady state response. Flux position, error in flux magnitude and error in torque are used as FLC state variables. The speed is estimated with model reference adaptive system(MRAS) based on artificial neural network(ANN) trained on-line by a back-propagation algorithm. This paper is controlled speed using hybrid fuzzy controller(HFC) and estimation of speed using ANN. The performance of the proposed induction motor drive with HFC controller and ANN is verified by analysis results at various operation conditions.

• Journal of Power Electronics
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• v.15 no.5
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• pp.1244-1255
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• 2015

This paper presents a new multi-machine robust control based on an electric differential system for electric vehicle (EV) applications which is composed of four in-wheel permanent magnet synchronous motors. It is based on a new master-slave direct torque control (DTC) algorithm, which is used for the control of bi-machine traction systems based on a speed model reference adaptive system observer. The use of an electric differential in the design of a new EV constitutes a technological breakthrough. A classical system with a multi-inverter and a multi-machine comprises a three-phase inverter for each machine to be controlled. Another approach consists of only one three-phase inverter for several permanent magnet synchronous machines. The control of multi-machine single-inverter systems is the subject of this study. Several methods have been proposed for the control of multi-machine single-inverter systems. In this study, a new master-slave based DTC strategy is developed to generate an electric differential system. The entire system is simulated by Matlab/Simulink. The simulation results show the effectiveness of the new multi-machine robust control based on an electric differential system for use in EV applications.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.574-577
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• 1996

In order to reduce the torque pulsation caused by non-sinusoidal flux distribution of the brushless direct drive motor(BLDDM), a new torque control technique is proposed. The linkage flux of the BLDDM is first estimated by using the model reference adaptive system (MRAS) technique and the instantaneous torque of the BLDDM is then estimated from the mathematical model including this estimated linkage flux. By using the estimated instantaneous torque of the BLDDM, the minor torque control loop to suppress the undesirable torque pulsation is designed. To show the effectiveness of the proposed control scheme, the simulations and experiments are carried out for the DSP-based BLDDM drive system with a power rate of 120W. It is well demonstrated from these results that the torque and speed control performance of the BLDDM is much improved by employing the proposed control scheme.