• The Transactions of the Korean Institute of Power Electronics
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• v.2 no.1
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• pp.39-45
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• 1997

In this paper, a high speed motor drive system using an indirect adaptive neural network controller is proposed. In the variable high speed motor drives, the speed response can be deteriorated by long settling time and high overshoot. To obtain a good dynamical performance, an adaptive feedforward controller consisted of Neural Network Controller(NNC) and Neural Network Emulator(NNE) is applied. The NNE is used to identify the parameters and characteristics of high speed motor. To train the controller, the weights are dynamically adjusted using the back propagation algorithm. Computer simulation and implementation of the proposed system is described.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1954-1955
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• 2007

This paper presents a modeling method of speed controller for DC motor drive system by using the Embedded Target for TI C2000 DSP in MATLAB/SIMULINK. Speed controller is easily designed and implemented by using the MATLAB/SIMULINK program, and speed control response and stability of the DC motor can be improved. Feedback of motor speed is processed through C28x QEP(Quadrature Encoder Pulse) from encoder pulse. The controller is designed as PI speed controller. Simulation program is drawn using SIMULINK. Then a real-time program for speed control of the DC motor is downloaded into the eZdsp F2811 control board. Speed control response is verified through simulations and experiments.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.3
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• pp.144-149
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• 2011

Currently, switched reluctance motors are studied to increase energy efficient. The switched reluctance motor is possible to control higher speed and torque than the induction motors and composition is simple. Current and rotor speed are considered to install the switched reluctance motor. In this paper, Simulink model of the switched reluctance motor is suggested and the adaptive controller is applied to the model for the speed control. Asymmetry converter including the IGBT is concerned with real-time control and the speed of switched reluctance motor is controlled by installing adaptive controller.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.3
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• pp.117-122
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• 2006

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also this paper is proposed. speed control of induction motor using FLC-FNN and estimation of speed using ANN controller. The back Propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. 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. The proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.216-218
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• 2006

The paper is proposed high performance control of induction motor drive with adaptive fuzzy logic controller(AFLC). Also, this paper is proposed speed control of induction motor using AFLC 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 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. The proposed control algorithm is applied to induction motor drive system controlled AFLC and ANN controller. And this paper is proposed the results to verify the effectiveness of the AFLC and ANN controller.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.282-284
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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, Speed controller of an induction motor based fuzzy-neural network 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.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.163-169
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• 2003

This study was carried out develope a motor power change speed device of motor by used micro- controller. This system was producted a auto-change speed device which switching frequency was 1,000MHz by used a auto- controller. It had a continuous output current such as 5A, 11A, 25A, 35A, 50A. It used a variable voltage from 9V to 18V(Maximum). We designed hardware of and software of micro-controller, we are made up of a auto cut-off function by 3.7V for detected power-loss prevention.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.82-89
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• 1997

In this paper, an adaptive speed controller with an FNN(Feedforward Neural Network) is proposed for servo motor drives. Generally, the motor system has nonlinearities in friction, load disturbance and magnetic saturation. It is necessary to treat the nonlinearities for improving performance in servo control. The FNN can be applied to control and identify a nonlinear dynamical system by learning capability. In this study, at first, a robust speed controller is developed by Lyapunov stability theory. However, the control input has discontinuity which generates an inherent chattering. To solve the problem and to improve the performances, the FNN is introduced to convert the discontinuous input to continuous one in error boundary. The FNN is applied to identify the inverse dynamics of the motor and to control the motor using coordination of feedforward control combined with inverse motor dynamics identification. The proposed controller is developed for an SR motor which has highly nonlinear characteristics and it is compared with an MRAC(Model Reference Adaptive Controller). Experiments on an SR motor illustrate te validity of the proposed controller.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.1027-1028
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• 2006

In this paper, design of current and speed controller for DC motor drive system using Embedded Target for TI C2000DSP in Matlab/Simulink is introduced. Current and speed controller is designed and implemented using program simply and easily, and speed control response of DC motor can be advanced. Current and speed control of DC motor is carried in eZdsp F2812 control board using Embeded Target for TI C2000DSP in Matlab/Simulink. Speed feedback is processed through A/D converter using tacho generator as speed sensor, and current feedback is processed through A/D converter using hall sensor as current sensor. Controller is designed to PI current controller and PI speed controller. Current and speed response is verified through simulations and experiments.