• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.3
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• pp.199-207
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• 2003

This paper is proposed new fuzzy controller for high performance of interior permanent magnet synchronous motor(IPMSM) drive. New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzily described situations in addition to the incremental control input calculated by conventional direct fuzzy controller The structures of the proposed controller is motivated by the problems of direct fuzzy controller. The direct controller generally give inevitable overshoot when one tries to reduce rise time of response especially when a system of order higher than one is under consideration. The undesirable characteristics of the direct fuzzy controller are caused by integrating operation of the controller, even though the Integrator itself is introduced to overcome steady state error in response. Proposed controller fuzzily clear out integrated quantities acrording to situation. This paper attempts to provide a thorough comparative insight into the behavior of IPMSM drive with direct and new fuzzy speed controller. The validity of new fuzzy speed controller is confirmed by response results for IPMSM drive system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.65-73
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• 2006

This paper presents speed control of IPMSM drive using neural network(NN) PI controller. 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, NNPI controller proposes a new method based neural network. NNPI 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.1
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• pp.40-49
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• 2008

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications and so of due to their excellent power to weight ratio. To obtain maximum efficiency in these applications, this paper proposes the neural network control method. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the error back propagation algorithm(EBPA) of neural network. The minimization of loss is possible to realize eHciency optimization control for the IPMSM drive. This paper proposes high performance and robust control through a real time calculation of parameter variation such as variation of back emf constant, armature resistance and d-axis inductance about the motor operation. Proposed algorithm is applied IPMSM drive system, prove validity through analysis operating characteristics con011ed by efficiency optimization control.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.3
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• pp.126-131
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• 2002

This paper is proposed to position and speed control of interior permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. The rotor position, which is an essential component of any vector control schemes, is calculated through the instantaneous stator flux position and an estimated flux value of rotating reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The validity of the proposed sensorless scheme is confirmed by simulation and its dynamic performance is examined in detail.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.478-479
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• 2012

This paper deals with 22kW IPMSM drive inverter for E-Tractor. First it introduces about hardware structure of inverter using developed MOSFET Module. Then it explains motor control algorithm. Also performance of IPMSM drive system is confirmed through experiments.

• Journal of Power Electronics
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• v.14 no.1
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• pp.74-81
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• 2014

In this study, a brain emotional learning-based intelligent controller (BELBIC) is developed for the speed control of an interior permanent magnet synchronous motor (IPMSM). A novel and simple model of the IPMSM drive structure is established with the intelligent control system, which controls motor speed accurately without the use of any conventional PI controllers and is independent of motor parameters. This study is conducted in both real time and simulation with a new control plant for a laboratory 3 ph, 3.8 Nm IPMSM digital signal processor (DSP)-based drive system. This DSP-based drive system is then compared with conventional BELBIC and an optimized conventional PI controller. Results show that the proposed method performs better than the other controllers and exhibits excellent control characteristics, such as fast response, simple implementation, and robustness with respect to disturbances and manufacturing imperfections.

• Proceedings of the KIEE Conference
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• 2002.11d
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• pp.183-186
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• 2002

The paper is proposed intantaneous torque control of IPMSM for drive of wide speed range. The control scheme is based on the mathematical model of the motor and is applicable to the constant torque and field weakening operations The scheme allows the motor to be driven with maximum torque per ampere (MTPA) characteristic below base speed and it maintains the maximum voltage limit of the motor wide field weakening and the motor current limit under all conditions of operation accurately. For each control mode. a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. The proposed control algorithm is applied to PMSM drive system for drive of wide speed range, the operating characteristics controlled by maximum torque control are examined in detail by simulation.

• Proceedings of the KIPE Conference
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• 1996.06a
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• pp.21-25
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• 1996

To control the speed of IPMSM drives it is necessary to know the speed and the rotor position. This is normally done by measurement of this values with electromechenical sensors. In this paper, a new approach to the position elimination method for the high performance variable speed IPMSM drives with the current controlled PWM technique is presented. For the high performance drive capability in the speed region, a Extended Kalman filter algorithm is adopted to estimate the rotor position as well as the angular velocity for the practical sensorless IPMSM drives. The high performance drive characteristics of the proposed method are verified using the wide simulation.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.210-212
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• 2006

This paper presents Hybrid PI(HBPI) controller of IPMSM drive using fuzzy adaptive mechanism control. 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, fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. 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.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.98-106
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• 2006

This paper proposes to position and speed control of interior Permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. Also, this paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of PMSM drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. A Gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor. A Gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.