• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.1
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• pp.47-57
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• 1991

A new control algorithm so called equal excursion sliding mode (EESM) control method is proposed to control the position of DC servo motor. This method introduces the concept of phase velocity vector that Filippov presented, and simplifies the problem of control gain selection in a conventional VSC strategy. And, by making state trajectories have equal excursions on both sides of switching hyperplane we minimized the probability of sliding mode's being collapsed, and approximated to the ideal sliding moed. Also, we proved the validity of this method by comparing the application results of this method to DC servo motor with those of conventional VSC strategy.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.312-313
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• 2008

로봇산업과 정밀기계산업을 포함한 많은 산입현장에서 서보모터를 이용한 기기 및 응용제품들이 다양하게 활용되고 있다. 이때 현장의 특성에 맞는 제어 시스템의 개발을 위해서나 사용 현장에서의 모터 동작 모니터링을 위해 제어가 편리한 사용자 친화적인 모니터링 시스템을 활용 한다면 업무 효율을 향상 시킬 수 잇다. 본 논문에서 개발한 DC모터 제어 및 모니터링 시스템은 임베디드 시스템을 기반으로 설계되었다. 이 시스템은 Intel PXA255 CPU를 장착하고 리눅스를 OS로 사용하였으며, 블루투스를 이용한 무선통신으로 모터 드라이버와 모니터링 및 제어에 필요한 데이터를 주고 받는다. 또한, 사용자 친화적인 GUI(Graphical User Interface)로 구성되어 조작 및 관리가 편리하다. 임베디드 기기의 특성상 시스템의 규모가 작고 무선 통신이 가능한 블루투스를 사용하였기 때문에 휴대성과 이동성이 뛰어나다는 장점이 있다. 이는 업무 효율의 향상을 기대할 수 있게 한다.

• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1185-1187
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• 1992

In this paper, PWM control is applied to the microprcessor-based adjustable speed dc motor drives. The motor drive system is composed of phase locked loop. Main drive circuit of the system is consisted of H-type bridge with switching transistors. PWM drive circuit is linearized by adding flywheeling diodes. And also. We study the optimum PWM data and period time so that it hase a nearly liner relationship between current and torque.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1115-1119
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• 2007

Five control methods (Speed Control, PID Gain Scheduling, Loop Time Control, Simple PID, Switching Control) have been applied to the control of an Inline Co-axial valve by the simulation of AMESim. The simulation results have shown that the speed control method is the most stable and the fastest way to reach to the set point in the simulation of the flow control. Moreover, It has been found that the five control methods have the almost same characteristics in the power consumption, the counter electromotive force, and the motor angular velocity. According to the analysis results, the fast and stable control characteristics of the speed control method is the most suitable for the flow control using a inline co-axial valve with a DC(BLCD) motor.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.212-220
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• 2004

The present DC Motor or STEP Motor have been used in electronic work and products. There are many papers 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 networks was used to improve the responding speed of controlling and measuring, and a new application was developed for the convenience of users. This paper showed that efficiency of controlling methodology by neural-network is superior to others in correctness and speed. We are intend to verify its practical usefulness though experimentations.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1044-1047
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• 1996

In this paper, GMDH(Group Method of Data Handling) algorithm, which is based on heuristic self organization to predict and identify the complex system, is applied to the control system of DC servo motor. The mathematical relation between input voltage and motor speed is obtained by GMDH algorithm. A design method of model following control system based on GMDH algorithm is developed. As a result of applying this method to DC servo motor, the simulation and experiment have shown that the developed method gives a good performance in tracking the reference model and in rejection of disturbance, in spite of constant load and changing load.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.125-128
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• 1989

This paper presents a DC servo motor controller using self-tuning PID algorithm, which can support Multi-processor for the real time processing. Computer simulation as well as experiment using Multi-processor(8088) are implemented with self-tuning PID algorithm. Presented algorithm is used to compare the performance of the controller with that of the classical PID controller through computer simulation and experiment. The result which use the Self-Tuning algorithm show that motor output follows the reference input trajectory fairly well inspite of load disturbances and parameter variations.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2721-2723
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• 1999

DC and small-signal ac characteristics are examined for a pulse-width modulated (PWM) dc-dc buck-boost converter with a peak voltage modulation (PVM) feedforward control. Circuit model is used to derive an expression for the output voltage in terms of the input voltage and load resistance. Small-signal circuit model is used to derive the input-to-output voltage transfer function (audiosusceptibility).

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.773-775
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• 1999

In this paper, A new approach to stable adaptive fuzzy control of systems is proposed. The proposed scheme does not require an accurate mathematical model yet it guarantees an asymptotic stability. Fuzzy logic system, which has the property of universal approximator is used as an adaptive element of the proposed controller. Also this Paper proposes a fuzzy system that estimates the maximum limit of the uncertain term in the system dynamics to guarantee the Lyapunov stability. Proposed adaptive fuzzy control is applied to the DC servo motor system in order to show its good performance.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.782-784
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• 1999

This paper deals with speed control of DC-servo motor using a Back-Propagation(BP) Learning Algorism and a PID controller Conventionally in the industrial control, PID controller has been used. But the PID controller produced suitable parameter of each system and also variable of PID controller should be changed enviroment, disturbance, load. So this paper revealed for experimental, a neural network and a PID controller combined system using developed speed characters of a Variable Load DC-servo motor. The parameters of the plant are determined by neural network perform on on-line system after training the neural network on off-line system.