• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.174-181
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• 1997

A proposed hybrid self-tuning control scheme for single rod hydraulic cylinder which has varying loads is presented here. An adaptive controller is developed for the system that use feedforward and P feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the hybrid self-tuning controller with a constant gain P contro- ller clearly shows its superior ability in handling load changes in quiescent states.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.2
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• pp.54-58
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• 2002

PID Controller is widely used as automatic equipment for industry. However, when a system has various characters, parameter decision and tuning for accurate control is a hard task. In this paper, expert auto-tuning PID controller using PLC is presented as away of solving this problem. Expert auto tuning algorithm is based on Ziegler-Nichols step response and expert knowledge. The test of control performance is carried out in practical speed control of Induction Motor in variable load, the experimental results suggest its superior performance.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.7
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• pp.1003-1011
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• 2009

This study aims at precise control of oil outlet temperature in the oil cooler system of machine tools for enhancement of working speed and processing accuracy. PID control logic is adopted to obtain desired oil outlet temperature of the oil cooler system with hot-gas bypass method. We showed that the gains of PID controller could be easily determined by using gain tuning methods to get the gain of PID controller without any mathematical model. We also investigated various gain tuning methods to design the gains of PID and compared each control performance for selecting the optimal tuning method on the hot gas bypass method through experiments. Moreover, we confirmed excellent control performance with proposed PI controller gain even though disturbances were abruptly added to the experimental system.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.644-649
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• 2006

In this paper, a methodology for estimating the model parameters of a discrete-time system and tuning a digital PID controller based on the estimated model and a genetic algorithm is presented. To deal with optimization problems regarding parameter estimation and controller tuning, pseudo-parallel genetic algorithms(PPGAs) are used. The parameters of a discrete-time system are estimated using both the model adjustment technique and a PPGA. The digital PID controller is described by the pulse transfer function and then its three gains are tuned based on both the model reference technique and another PPGA. A set of experimental works on two processes are carried out to illustrate the performance of the proposed method.

• Journal of KSNVE
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• v.8 no.3
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• pp.441-449
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• 1998

A self-tuning control scheme, incorporated with the simplified 1st-order ARMAX(Auto-Regressive Moving Average eXogenous) model, for single rod hydraulic cylinder which has varying dynamic characteristics is presented here. An adaptive controller is developed for the system that uses feedforward and optimal feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the self-tuning controller with a fixed gain proportional controller clearly shows its superior ability in handling load changes in quiescent states.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.229-229
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• 2000

Conventional gain-tuning methods such as Ziegler-Nickels methods, have many disadvantages that optimal control ler gain should be tuned manually. In this paper, modified PID controllers which include self-tuning characteristics are proposed. Proposed controllers automatically tune the PID gains in on-1ine using neural networks. A new learning scheme was proposed for improving learning speed in neural networks and satisfying the real time condition. In this paper, using a nonlinear mapping capability of neural networks, we derive a tuning method of PID controller based on a Back propagation(BP)method of multilayered neural networks. Simulated and experimental results show that the proposed method can give the appropriate parameters of PID controller when it is implemented to DC Motor.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.351-354
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• 2001

In this paper, we present self-tuning control of switched reluctance motor for maximum torque with phase current and shaft position sensor. Determination method of turn-on/off angle is realized by using self-tuning control method. During the sampling time, micro-controller checks the number of pulse from encoder and compare with the number of pre-checked pulse. After micro-controller calculates between two data, it moves forward or backward turn-off angle. When the turn-off angle is fixed optimal turn-off angle, the turn-on angle automatically moves forward or backward by a step using self-tuning control method. And then, optimal turn-off angle is searched once again. As such a repeating process, turn-on/off angle is moved automatically to obtain the maximum torque. The experimental results are presented to validate the self-tuning algorithm.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.8 s.101
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• pp.954-961
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• 2005

This paper is concerned with the implementation of auto-tuning positive position feedback controller using a digital signal processor and microcontroller. The main advantage of the positive position feedback controller is that it can control a natural mode of interest by tuning the filter frequency of the positive position feedback controller to the natural frequency of the target mode. However, the positive position feedback controller loses its advantage when mistuned. In this paper, the fast fourier transform algorithm is implemented on the microcontroller whereas the positive position feedback controller is implemented on the digital signal processor. After calculating the frequency which affects the vibrations of structure most, the result is transferred to the digital signal processor. The digital signal processor updates the information on the frequency to be controlled so that it can cope with both internal and external changes. The proposed scheme was installed and tested using a beam equipped with piezoceramic sensor and actuator. The experimental results show that the auto-tuning positive position feedback controller proposed in this paper can suppress vibrations even when the target structure undergoes structural change thus validating the approach.

• Journal of Photoscience
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• v.10 no.3
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• pp.257-261
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• 2003

We have systematically studied the evolution of the photoluminescence(PL) tuning of porous silicon(PS) by electrochemical etching in various mixed electrolytes. The electrolytes employed as an etchants were mixtures of HF:CH$_3$COOH:HNO$_3$:C$_2$H$\_$5/OH solutions where the composition ratios (%) were varied from 10:1.98:0:88.02 to 10: 1.98:8.4:79.62 under constant concentration of HF and CH$_3$COOH with a total volume of 100 ml. Changes in the surface morphology of the samples caused by variations in the etching process were investigated by scanning electron microscopy (SEM) and atomic force microscopy (AFM). After samples are etched in various mixed electrolytes, FTIR analyses show that there is the non-photoluminescent state and the photoluminescent state simultaneously. The PL spectra show the PL tuning in the ranging from 560 to 700 nm with the increase of HNO$_3$ concentration. An analysis of the subsequent PL relaxation mechanism was carried out by time-correlated single photon counting (TCSPC) method. Based on experimental results, it is assumed that a red shift of the main PL peak position is related to the HNO$_3$ activated formation of silicon oxygen compounds. Therefore, the use of electrolyte mixtures with composition ratios can be obtained adequate and reproducible results for PL tuning.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.95-103
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• 2001

The purpose of Introducing a combined cycle with gas turbine in power plants is to reduce losses of energy, by effectively using exhaust gases from the gas turbine to produce additional electricity or process. The efficiency of a combined power plant with the gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a combined 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul, Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controllers.