• Proceedings of the Korean Society of Precision Engineering Conference
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• 1991.04a
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• pp.158-165
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• 1991

DC servo motors have small torques compared to their weight. In order to reduce the speed and increase the output torque of the DC motor, a gear box is commonly used. The use of a gearbox, however, imposes limitations onmany applications because of the backlash and the reduction in transmission efficiency. Furthemore, the elastic deformation or the compliance of the gearbox decreases the accuracy of the servo mechanism and the stability of the system. In view of the many disadvantages in using the gearbox, a more effective solution has to be found. The solution is the direct drive mechanism. There are many kinds of direct drive motors. I will consider the ultrasonic motor in particular.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.252-257
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• 2002

We designed a neuro-fuzzy controller to improve some problems that are happened when the DC servo motor is controlled by a PID controller or a fuzzy logic controller. Our model proposed in this paper has the stable and accurate responses, and shortened settling time. To prove the capability of the neuro-fuzzy controller designed in this paper, the proposed controller is applied to the speed control of DC servo motor. The results showed that the proposed controller did not produce the overshoot, which happens when PID controller is used, and also it did not produce the steady state error when FLC is used. And also, it reduced the settling time about 10%. In addition, we could by aware that our model was only about 60% of the value of current peak of PID controller.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2255-2257
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• 2002

In this paper, Fuzzy-Observer is designed to control the speed of DC Servo Motor. Fuzzy-Observer estimates the speed of DC Servo Motor with the measurement of the amature current. The constant speed and variable speed experiments are excuted to evaluate the performance of Fuzzy-Observer.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.852-854
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• 1995

This paper proposes a new identification method that utilizes fuzzy inference in parameter identification. The prosed system has an additional control loop where a real plant has replaced by a plant model. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. In this paper, the tuning method which determines parameters of PID controller automatically is described through applying this algorithm to DC servo motor. And we intend to investigate effectiveness of the method by experiments. This method is effective in auto-tuning because the response of the closed loop has verified. The simulated and the experimental results of the dc servo motor are shown to confirm the viability of this method.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.855-858
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• 1995

A neural network has very simple construction (input, output and connection weight) and then it can be robusted against some disturbance. In this paper, we proposed a neuro-controller using a Multi-Layered neural network which is combined with PD controller. The proposed neuro-controller is learned by backpropagation learning rule with momentum and neuro-controller adjusts connection weight in neural network to make approximate dynamic model of DC Servo motor. Computer Simulation results show that the proposed neuro-controller's performance is better than that of origianl PD controller.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.56-62
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• 1999

We make a study of pricisioning apparatus that is used in the various industrial machine. The study was carried out to develope a pricision positioning apparatus, consisting of servo motor and piezoelectric actuator. This system is composed of fine and coarse apparatus, measurement system and control system. Piezoelectric actuator is designed for fine positioning. Coarse positioning using lead screw is drived by servo motor. Control system output a signal from laser interferometer and microsense to amplifier of servo motor and piezoelectric actuator after digital signal processing(DSP). Resolution of this apparatus measure with laser interferometor and microsense so, we can controlled positioning of one output by the coarse positioning in the system. Also we obtain the positioning resolution of 9nm in the system.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.51-59
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• 1997

In this paper, we perform the position control of a DC servo motor using fuzzy neural controller. We use the Fuzzy controller for the position control, because the Fuzzy controller is designed simpler than other intelligent controller, but it is difficult to design for the triangle membership function format. Therefore we solve the problem using the BP learning method of neural network. The proposed Fuzzy neural network controller has been applied to the position control of various virtual plants. And the DC servo motor position control using the fuzzy neural network controller is performed as a real time experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.3
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• pp.213-220
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• 1990

DC servo motor has been often used as the position control system, because the performance is excellent on the velocity and position control system. When the unknow disturbance and accessible load torque are imposed on the position control of DC servo motor, this system has the steady and/or transient state error. In this paper, a new method which has high stiffness for reducing the error is proposed. This error will be reduced by acceleration control. The effectiveness of the acceleration control is confirmed by using computer simulation.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1132-1134
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• 2003

This paper presents the realization of the vector control for AC servo motor using a high performance DSP, TMX320F2812. This DSP has some special peripheral circuits to drive a AC Servo motor as AD converter, QEP and so on. It makes us reduce the time of developing a control system and also can be simple size controller. The vector control algorithm for instantaneous torque control and SVPWM algorithm by offset voltage methods is adopted and we got the satisfactory results.

• Journal of Engineering Education Research
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• v.17 no.5
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• pp.17-22
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• 2014

Unmanned aerial vehicles (UAVs) that have been recently commercialized can largely be divided into fixed-wing aircraft and rotor aircraft by their styles and flight characteristics. Although the fixed-wing aircraft represents higher power efficiency, higher speed, longer flight distance and larger loading weight than the rotor aircraft, they have a disadvantage of requiring a space for take-off and landing. On the other hand, the rotor aircraft can implement vertical take-off and landing (VTOL) and represents various flight modes (hovering, steep bank turns and low-speed flights). But they require both precision take-off control and attitude control. In this study, we used a quad-tilt rotor UAV to combine advantages in both the fixed-wing aircraft and the rotor aircraft. The quad-tilt rotor (QTR) system was designed and constructed by adding a tilt device with a servo motor to a general quad-rotor vehicle.