• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.173-183
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• 1998

In this paper, an auto-tuning method for fuzzy controller's membership functions based on the neural network is presented. The neural network emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and the reformed fuzzy controller uses for speed control of induction motor. Thus, in the case of motor parameter variation, the proposed method is superior to a conventional method in the respect of operation time and system performance. 32bit micro-processor DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzzy control algorithm. Through computer simulation and experimental results, it is confirmed that the proposed method can provide more improved control performance than that PI controller and conventional fuzzy controller.

• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.152-155
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• 1997

This thesis proposed a speed control system for induction motors robust to variations in torque and parameters by feedforward compensating the current portion of load torque, adding a load torque observer to the conventional PI controller in the indirect vector controlled induction motor system. In conclusion, this thesis demonstrate the improved transient characteristic to variations in reference speed and load torque, compared to the conventional PI control method, by means of the feedworward control of the estimated load torque.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.526-531
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• 2012

This paper, we describe the vector control of surface mounted PMSM (Permanent Magnet Synchronous Motor) using the fuzzy controller which is suggested algorithm. In these days, when vehicle is operated or not, whether the road is covered or not, the sensitivity of the steering column is not stable. To make up for it, the PI gain of a steering column controller is adjusted by experience. It becomes the price because it need a lot of sensor. Also it is difficult to implement robust control because we need a lot of parameters for variable road conditions which are the off road, the on road, a low battery voltage, a high battery voltage, a vehicle speed. In this paper, we propose fuzzy controller using the suggested algorithm which suitable for steering system. We test the fuzzy controller with the various condition. We get the good performance of fuzzy controller even if it is nonlinear system. We check a robust the fuzzy controller using the suggested algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.219-225
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• 2014

The purpose of this paper is to control of the low-speed, high-precision PMSM 2-axes pitch/turning. In this paper, apply the PAM-PWM inverter for it. However, The PAM-PWM inverter, control algorithms and hardware is complex. But it is possible to improve the performance in the low-speed operation can reduce the effect of the PWM ripple and Dead Time of inverter by applying suitable DC-bus voltage control. The direct driver PMSM(Permanent Magnet Synchronous Motor) configured to vector control part, PAM control part and the other controller. The vector control part includes PI current, speed control, additional space vector modulation. PAM control part has to have PI voltage controller and P current controller for DC-bus voltage control. Besides, the motor position estimator, the speed estimator and the counter electromotive force and Dead Time Compensation are added. With this arrangement, PMSM was driven with a low pole pitch/turning by performing the current control to the current command or torque command is the paper. As a result, it was possible to minimize the disturbance component that appears in the drive in proportion to the DC voltage magnitude. The use of a hydraulic drive method for a two-axis bubble column is a typical tank. When using the PWM PAM inverter driver is in the turret can be driven by high-precision, low vibration, low noise compared to the hydraulic drive may contribute to the computerization of the turret.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1051-1052
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• 2006

This paper deals with mathmatical of an induction motor, considering non-linearity in the torque balance equation under closed loop operation with a reference speed. A controller based on Adaptive Nuro-Fuzzy Inference System (ANFIS) is developed to minimize overshoot and settling time following sudden changes in load torque. The overall system is modeled and simulated using the Matlab/simulink and Fuzzy Logic Toolbox. The advantages of fuzzy logic and neural network based fuzzy logic controller. Required training data the ANFIS controller is generated by simulation of the anti-windup PI controller is eliminated using the ANFIS controller. The transient deviation of the response from the set reference following variation in load torque is found to be negligibly samll along with a desirable reduction in settling time for the ANFIS controller.

• Journal of Power Electronics
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• v.10 no.2
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• pp.194-202
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• 2010

The main cause of degradation in an unbalanced stand-alone doubly-fed induction generator (DFIG) system is negative sequence components that exist in the generated stator voltages. To eliminate these components, a hybrid current controller composed of a proportional-integral controller and a resonant regulator is developed in this paper. The proposed controller is applied to the rotor-side converter of a DFIG system for the purpose of compensating the negative stator voltage sequences. The proposed current controller is implemented in a single positive rotating reference frame and therefore the controller can directly regulate both the positive and negative sequence components without the need for sequential decomposition of the measured rotor currents. In terms of compensation capability and accuracy, simulations and experimental results demonstrated the excellent performance of the proposed control method when compared to conventional vector control schemes.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.65-68
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• 2001

In the vector control methods of induction motor, the stator current is divided into the flux and torque component current. By controlling these components respectively, the methods control independently flux and torque as in the DC motor and improve the control effects. To apply the vector control methods, the position of the rotor current is identified. The indirect vector control use the parameters of the machine to identify the position of rotor flux. But due to the temperature rise during machine operation, the variation of rotor resistance degrades the vector control. To solve the problem, the q-axis is aligned to reference frame without phase difference by comparing the real flux component with the reference flux component. Then to compensate the slip, PI controller is used. The proposed method keeps a constant slip by compensating the gain of direct slip frequency when the rotor resistance of induction motor varies. To prove the validations of the proposed algorithm in the paper, computer simulations is executed.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.516-518
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• 1999

This paper presents an feed-forward neural network design instead PI controller for the speed control of an Induction Motor. The design employs the training strategy with Neural Network Controller(NNC) and Neural Network Emulator(NNE). Emulator identifies the motor by simulating the input and output map. In order to update the weights of the Controller. Emulator supplies the error path to the output stage of the controller using backpropagation algorithm. and then Controller produces an adequate output to the system due to neural networks learning capability. Therefore it becomes adjustable to the system with changing characteristics caused by a load. The speed control based on neural networks for induction motor is implemented by a vector controlled induction motor. The simulation results demonstrate that actual motor speed with neural network system well follows the reference speed minimizing the error and is available to implement on the vector control theory.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.10
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• pp.443-445
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• 2006

Generally PI controller is used to control the speed of an induction motor. It has the good performance of speed control in case of adjusting the control parameters. But it occurred the problem to change the control parameters in the change of operation condition. In order to solve this problem, Fuzzy control or Artificial neural network is introduced in the speed control of an induction motor. However, Fuzzy control have the problems as the difficulties to change the membership function and fuzzy rule and the remaining error Also Neural network has the problem as the difficulties to analyze the behavior of inner part. Therefore, the study on the combination of two controller is proceeded. In this paper, Fuzzy-neural controller to make up these controllers in parallel is proposed and the speed control of an induction motor is performed using the proposed controller Through the experiment, the fast response and good stability of the proposed speed controller is proved.