• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.409-412
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• 2000

This paper investigates a novel speed identification of induction motor using 2 layer neural networks. The proposed control strategy is based on neural networks using model of full order state observer. in the proposed neural networks system the error between the desired variable and the adaptive variable is back-propagated to adjust the rotor speed, So that the adaptive variable will coincide with the desired variable. The proposed control algorithm is verified through simulation and experiment using th digital signal processor of TMS320C31

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.164-170
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• 2010

In brushless DC motor, current flow should be controlled such that only properly selected 2 out of 3 phases carry current depending on the position of rotor. In order to detect position of rotor, hole sensor, encoder, optical position-detecting sensor, and magnetic position-detecting sensor are frequently employed. These sensors not only often cause malfunction in low and high temperature but they also have disadvantage of increasing cost and size of an motor system. To reduce the cost and size and to increase the robustness of the motor system, recently researches on sensorless motor dirve are very active. This paper proposes a novel unipolar PWM switching method that can improve the control problem caused by the difficulty of detecting zero crossing point at high revolution speed by minimizing the switching noise while increasing the lifespan of the drive system.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.260-262
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• 1998

A new method of induction motor drive, which requires not shaft encoder, is presented. This system has both torque and speed controls that are performed by vector control. The scheme is on the basis of a rotor flux speed control, which is performed by torque producing current and rotor flux, derived from the stator voltages and currents. But, there is a problem with respect to the calculated rotor flux vector, which is an integrating operation by which the rotor induced voltage is converted into the rotor flux. The calculated rotor flux does not work so that it is unstable in initial operation, as motor speed approaches zero. For the proposed rotor flux estimator, a lag circuit is employed, to which both the motor-induced voltage and rotor flux command are imposed, and it is possible to calculate even a low frequency down to standstill. We show the validity of the proposed control method through several computer simulations.

• 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.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.4B no.3
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• pp.108-113
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• 2004

This paper presents methods to improve performance of the power supply system in a NASA deep space explorer. In the Stirling engine driven reciprocating Brushless DC (BLDC) generator, the accurate position information of the prime mover is important to diagnose the performance of the engine and prevent distortion of the output power. Since sensors to detect the position are fragile and unreliable, and conventional sensorless techniques have drawbacks in the low speed region, a novel sensorless position detection technique for the prime mover has been proposed and verified. Another major issue of the generator for the spacecraft is power density maximization. The mass of the power system is important to the mass of the satellite. Therefore, the components of the spacecraft should be lightweight. Conventional rectification methods cannot achieve the maximum power possible due to non-optimal current waveforms. The optimal current waveform for maximizing power density and minimizing machine size and weight in a nonsinusoidal power supply system has been derived, incorporated in a control system, and verified by simulation work.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.140-143
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• 1991

This paper describes a compensation method for the rotor resistance variation of induction machines in speed sensor-less vector control system using MRAS(model reference adaptive system). In case of rotor resistance variation, the analysis of the conventional speed sensor-less vector control system using MRAS is presented and the compensation method for rotor resistance variation using Fuzzy logic is proposed. In order to confirm the performance of the proposed algorithm, computer simulation is performed.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2177-2178
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• 2011

In this paper, adaptive speed sensorless vector control, sliding mode observer to be present. Adaptive sliding mode observer of the motor stator coordinate system using the voltage equations of the rotor flux components are observed. Lyapunov function of the induction motor speed is estimated by the relationship further. In order to establish such a control scheme based on the way conventional PI controller and sliding mode observer annexing characteristics of the system through simulation and experiment were compared. Analyzed and compared according to the results presented confirmed the usefulness of the system.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.179-181
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• 2004

This paper is proposed an adaptive fuzzy-neural network(A-FNN) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using A closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.311-315
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• 2007

In this paper, a new approach for the Synchronous Reluctance Motor control which ensures producing Maximum Torque per Ampere(MTPA) over the entire field weakening region is presented. In addition, This paper presents a speed sensorless control scheme of SynRM using artificial neural network. Also, by adjusting the base speed for the field weakening operation according to the flux level, the current and voltage limit, the smooth and precise transition into the field weakening operation can be achieved The proposed scheme is verified validity through simulation.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.177-180
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed estimation and control of speed of induction motor using ANN Controller. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.