• Journal of Advanced Marine Engineering and Technology
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• v.31 no.4
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• pp.441-447
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• 2007

The speed and torque control performance of the DC motor used in the industrial field is affected by the change of parameters. In particular the change of armature resistance can be greatly originated from various load conditions. Accordingly a large number of studies to estimate those problems in the servo motor control field have already been under way. In this paper, the armature resistance on the DC motor under several load and speed conditions is estimated by the Artificial Neural Network(ANN), and the validity is proven by the speed estimation of sensorless speed control system.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1021-1023
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• 1996

This paper proposes a design of self-tuning fuzzy rules and membership functions based on genetic algorithms. Sub-optimal fuzzy rules and membership functions are found by using genetic algorithms. Genetic algorithms are used for tuning fuzzy rules and membership functions. A arbitrary speed trajectories are selected for the reference input of the proposed methods. Experimental results show the good performance in the DC motor control system with the self-tuning fuzzy controller based on genetic algorithms.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2245-2247
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• 2003

The present DC Motor or STEP Motor have been used in electronic work or products. There have been researches that let those Motor improved more conveniently in controlling and measuring those than before. By controlling and measuring those, the convenience of users and the functions of products can be improved. In addition, the responding speed of whole system can be increased by improving it of controlling and measuring. Therefore it is necessary that we develop motor motion application. Because of this necessity, Neural-Network was used to improve the responding speed of controlling and measuring, and a new application was developed for the convenience of users. This thesis showed efficiency of controlling methodology by Neural-Network superior to others in correctness and speed. We are intend to verify its appropriateness though experimentations.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.248-250
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• 1993

In this paper, we assume that the dynamics of DC motor and nonlinear load are unknown. We train the inverse dynamic model of DC motor and nonlinear load using the neural network and construct speed control system based on the traind dynamic model and current control mode. Speed prediction scheme using neural network is also proposed the alleviate the time delay effect caused by the computation time of neural network. Simulation results show good performances of the control system. Finally, hardware configuration of the control system is outlined.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.46-48
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• 1998

In this paper, axial type double rotor brushless DC motor is designed where the rotor is located at the both sides of stator. The rotor uses rare-earth magnets of 16 poles and the stator has 12 coils. The genetic algorithm is used to optimize the efficiency of the designed motor. The characteristics of the design parameters are estimated by varying them for the maximum efficiency.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.1
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• pp.48-56
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• 2006

This paper studies particularly applicable method for sensorless PM BLDC motor drive system. The waveform of the motor internal voltages(or back emf) contains a fundamental and higher order frequency harmonics. Therefore the third harmonic component is extracted from the stator phase voltage. The resulting third harmonic signal keeps a constant phase relationship with the rotor flux for any motor speed and load condition. Also because of low resolution of estimated signal obtained by the proposed sensorless algorithm, to improve the wide range of speed response characteristic more exactly, we propose the rotor position signal synthesizer using PLL circuit based on estimated signals. Some experimental results are provided to demonstrate the validity of the proposed control method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.10
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• pp.911-920
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• 2016

For the pitch and yaw axis attitude control of launch vehicle, thrust vector control which changes the direction of thrust during the engine combustion is commonly used. Hydraulic actuation system has been used generally as a drive system for the thrust vector control of launch vehicles with the advantage of power-to-weight ratio. Nowadays, due to the developments of highly efficient electric motor and motor control techniques, it has done a lot of research to adopt electro-mechanical actuator for thrust vector control of small-sized launch vehicles. This paper describes system design and test results of the prototype of direct drive electro-mechanical actuation system which is being developed for the thrust vector control of $3^{rd}$ stage engine of KSVL-II.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.353-360
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• 2002

Methods for automatic tuning of PID controllers have been on of the results of the active research on control. The proposed controller also is auto-tuning of PID controller The proposed immune algorithm has an uncomplicated structure and memory-cell mechanism as the optimization algorithm which imitates the principle of humoral immune response. We use the proposed algorithm to solve optimization of PID controller parameters. Up to now, the applications of immune algorithm have been optimization problems with non-varying system parameters. Therefore the usefulness of memory-cell mechanism in immune algorithm is without. And research of memory-cell mechanism does not give us entire satisfaction. This paper proposes the immune algorithm using a memory-cell mechanism which can be the application of system with nonlinear varying parameters. To verify performance of the proposed immune algorithm, the speed control of nonlinear DC motor are performed. The results of Computer simulations represent that the proposed immune algorithm shows a fast convergence speed and a good control performances under the varying system parameters.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.2
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• pp.112-118
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• 2004

Recently, development of rare earth permanent magnet with the high remanence, high coercivity allows the design of brushless motors with very high efficiency over a wide speed range. Cogging torque is produced in a permanent magnet by magnetic attraction between the rotor mounted permanent magnet and the stator teeth. It is an undesired effect that contributes to output ripple, vibration, and noise of machine. This cogging torque can be reduced by variation of magnet arc length, airgap length, magnet thickness, shifting the magnetic pole and varying the radial shoe depth and etc. In this paper, some airgap length and magnet arc that reduce cogging torque are found by finite element method(FEM) and Maxwell stress tensor method. The SPM(Surface Permanent Magnet) type of high-power Brushless DC (BLDC) motor is optimized as a sample model.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.2
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• pp.194-204
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• 2002

In this paper, a new two-phase space vector RPWM(Random PWM) is proposed. In the proposed RPWM, each of two-phase PWM pulses is located randomly in each switching interval. Based on the space vector modulation technique, the duty ratio of the pulses is calculated. Along with the randomization of the PWM pulses, we can obtain the effects of spread spectra of inverter output voltage, d.c link current and audible switching acoustic noise as in the case of randomly changed switching frequency. To verily the validity of the proposed two-phase RPWM scheme, the experiment based on the Cl67 micro-controller was executed. The performance of the proposed scheme was compared with traditional PWM schemes experimentally.