• Proceedings of the KIEE Conference
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• 1992.07b
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• pp.1179-1181
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• 1992

A discrete Pl controller is implemented easily using a micro-processor, and it can be confirmed to a adaption of a system and real time processing. In this paper, a speed controller by discrete Pl control using a IBM PC/AT(12MHz) as a micro-processor is implemented and applied to a DC servo motor. In designing the discrite Pl controller, a sampling time and a speed is accepted from key-board, and is processed the control coefficient automatically, and than calculate the gain. Therefore the speed of a DC servo motor is obtained and controlled regulaly. The designed and manufactured discrete Pl control system is experimented. The result shows the good response at the 60 RPM to 250 RPM on the load using the load-spring. The speed error is under 1% on the steady load, but nearly 2-3% on the transient load.

• 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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• 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.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.269-272
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• 1992

In this paper, an implementation approach of Fuzzy Position Controller for DC servo motor which requires the faster and more accurate dynamics is presented. The proposed Fuzzy position controller is consists of an adjustment routine obtaining optimal scale factors and a Fuzzy control routine inferencing optimal control signals, using 80286 microprocessor and DT 2801 board. Comparing to conventional PD controllers, the control performances such as reaching time, overshoot, disturbance adaptability and etc. are substantially improved.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.28 no.1
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• pp.39-44
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• 1992

Analog PID controllers have been designed to make good use of position control in industries. Recently, the importance of digital position control is emphasized for the requirements of controller which are not only to control the objects but to include various aspects such as easiness of design and implementation, simple exchange of control program and convenient communications of data between various controllers and a host computer. This study proposes a combined control method which is mixed the vaiable structure control (VSC) with the PI control for minimum time position control of DC servo motor by microcomputer. The results of test by this method show offset-free and minimum time optimal position control which is not affected by the disturbance and the system parameter variations. The validity of the proposed method comparing with the conventional PID control is proved by the response experiments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1995.10a
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• pp.18-23
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• 1995

The study was carried out to develope a precision positioning apparatus, consisting of DC 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 DC servo motor. Control system output a signal from laser interferometer and microsense to amplifier of DC servo motor and piezoelectric actuator after digital signal processing(DSP). Resolution of this apparatus measure with laser interferometor and microsense

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.2
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• pp.48-54
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• 2002

In this study, a neuro-fuzzy controller which has the characteristic of fuzzy control and artificial neural network is designed. A fuzzy rule to be applied is automatically selected by the allocated neurons. The neurons correspond to fuzzy rules are created by an expert. To adapt the more precise model is implemented by error back-propagation learning algorithm to adjust the link-weight of fuzzy membership function in the neuro-fuzzy controller. The more classified fuzzy rule is used to include the property of dual mode method. In order to verify the effectiveness of the proposed algorithm designed above, an operating characteristic of a DC servo motor with variable load is investigated.

• 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.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.