• Laser Solutions
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• v.9 no.2
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• pp.17-22
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• 2006

In this study, PID control method was applied to decrease the power fluctuation of the pulse laser which is one of the major processing variables in laser machining process. To stabilize the power fluctuation of the pulse laser, we averaged 10 pulse outputs of Nd:YAG laser operating in 10Hz using boxcar averager, and with taking this averaged output as an input signal, we conducted PID control using optical attenuator which is consisted of half wave plate attached on the stepping motor and polarizer. When PID control was not enabled, the power fluctuation was 4.71% and with PID control, the power fluctuation was 1.86% for 2 hours and 1 hour respectively. As a result, we stabilized the power fluctuation of the pulse laser by 60.5%

• Proceedings of the Korean Society of Laser Processing Conference
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• 2006.06a
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• pp.89-96
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• 2006

In this study, PID control method was applied to decrease the power fluctuation of the pulse laser which is one of the major processing variables in laser machining process. To stabilize the power fluctuation of the pulse laser, we averaged 10 pulse outputs of Nd:YAG laser operating in 10Hz using boxcar averager, and with taking this averaged output as an input signal, we conducted PID control using optical attenuator which is consisted of half wave plate attached on the stepping motor and polarizer. When PID control was not enabled, the power fluctuation was 4.71% and with PID control, the power fluctuation was 1.86% for 2 hours and 1 hour respectively. As a result, we stabilized the power fluctuation of the pulse laser by 60.5%

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1380-1385
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• 2004

In this paper, auto-tuning technique of the PID controller gain by particle swarm optimization algorithm is presented. PID controller is easy to implement to numerous control systems. After PID gain tuning is completed, its result could be implemented to control spacecraft vibration such as jitter that is high frequency vibration usually over 10Hz. The off-line PID controller tuning is done under system nonlinearities and uncertainties existence, then its result is applied to control experiment device to prove the PSO efficiencies.

• Journal of KIEE
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• v.10 no.1
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• pp.16-22
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• 2000

The Main role of the gas turbine lies in the utilization of waste heat which may be found in exhaust gases from the gas turbine or at some other points of the process to produce additional electricity. Up to date, the PID controller has been used to operate under such difficult conditions, but since the gain of PID controller manually experience. In this paper parameter separation type 2-DOF PID controllers are proposed based on the gas turbine control system. Gas turbine transfer function is achieved from operation data of Gun-san gas turbine and Tuning algorithms of parameter separation type 2-DOF PID controller is ANFIS. Results represents satisfactory response.

• Journal of Sensor Science and Technology
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• v.8 no.3
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• pp.259-264
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• 1999

The $CO_2$ measuring system using infrared sensor has the variance according to the temperature change. Therefore, the temperature compensation should be needed to obtain a reliable measurement. In this study, the sensor module consist of infrared $CO_2$ Sensor, IR Source, pipe and the heater and measuring system has amplifier, A/D converter and microprocessor. And we suggest a method to reduce the error by using the PID temperature control. We use optimum parameters setting of Ziegler & Nichols as well as PID temperature control algorithm for the temperature compensation. In this method, PID optimum parameter is set from dummy time(L) and maximum slope(R). As a result of using this PID temperature control, it is founded that it has the fast response and low steady state error. Therefore, it is certainly proved that this is very suitable algorithm to correct the error on measurement.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.25-33
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• 1997

This study deals with controlling the velocity of Electr-Hydraulic servo system through the non-stan-dard PIC control. This was done as follows. First, we modeled nonlinearised model and linearised model, second designed analytic program for electro-hydraulic servo system velocity control Lastly, to im- prove dynamic characteristics of system we designed non-standard PID contoller and verifed throughth experi- ment and MATLAB program, commercial used software.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.326-329
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• 1995

PID control has been widely used for real control system Further, there are muchreasearches on control schemes of tuning PID gains. However, there is no results for discrete-time systems with unknown time-dealy and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown parameters and unknown tiem-delay system. A numerical simulation was presented to illuatrate the effectiveness of this method.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.165-168
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• 2003

In this paper the design of the model following control system is proposed using the PID control structure. The games of the PID controller in the proposed control system are automatically adjusted by back-propagation algorithm of the neural network. And applying to the position control system, it's performance is verified through the results of computer experiment.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.85-89
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• 2004

Robust control for feedback control system is needed according to the highest precision of industrial automation. However, when a neural network feedback control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem, in this paper, hybrid control method of neural network controller and PID controller is presented. A neural network controller is operated as a main controller, a PID controller is a assistant controller which operates only when some undesirable phenomena occur, e.q., when the error hit the boundary of constraint set. The robust control function of neural network-PID hybrid controller is demonstrated by speed control of Motor.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.1
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• pp.63-66
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• 1995

PID controller is being used in many servo control system. However, when a control system has variable load, it is difficult to guarantee the accurate control of the system. In the way of solving this problem, in this paper, a auto-tuning method of PID controller parameter using fuzzy rule in variable load is presented. The parameter of PID controller are decided by fuzzy rule according to load variation. The accurate control function of fuzzy auto-tuning is demonstrated by simulation.