• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.290-294
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• 2014

PID(Proportional, Integral, Derivative) controller is the most popular process controllers in nuclear power plants. The optimized parameter setting of the process controller contributes to the stable operation and the efficiency of the operating nuclear power plants. PID parameter setting is tuned when new process control systems are installed or current process control systems are changed. When the nuclear plant is shut down, a lot of PID tuning methods such as the Trial and Error method, Ultimate Oscillation method operation, Ziegler-Nichols method, frequency method are used to tune the PID values. But inadequate PID parameter setting can be the cause of the unstable process of the operating nuclear power plant. Therefore the results of PID parameter setting should be simulated, optimized and finally verified. This paper introduces the simulation method of PID tuning to optimize the PID parameter setting and confirms them of the actual PID controller in the operating nuclear power plants. The simulation method provides the accurate process modeling and optimized PID parameter setting of the multi-loop control process in particular.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.423-426
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• 2005

In this paper, we proposed a PID tuning algorithm by the fuzzy set theory to improve the performance of the PID controller. The new tuning algorithm for the PID controller has the initial value of parameter Kp, $\tau_{I}$, $\tau_{D}$. by the Ziegler-Nichols formula that uses the ultimate gain and ultimate period from a relay tuning experiment. We will get the error and the error rate of plant output corresponding to the initial value of parameter and fnd the new proportion gain(Kp) and the integral time ($\tau_{I}$) from fuzzy tuner by the error and error rate of plant oueut as a membership function of fuzzy theory. This fuzzy auto tuning algorithm for PID controller considerably reduced the overshoot and rise time as compared to any other PID controller tuning algorithms. And in real parametric uncertainty systems, it constitutes an appreciable improvement of performance. The significant property of this algorithm is shown by simulation

• Transactions of Materials Processing
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• v.14 no.4 s.76
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• pp.327-337
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• 2005

In the present work, the two back stress kinematic hardening models are proposed by combining Armstrong-Frederick, Phillips and Ziegler's hardening rules. Simple combination of hardening rules using simple rule of mixtures results in various evolutions of the kinematic hardening parameter. Using the combined hardening models the ultimate back stress fur the present models is also derived. The stress rate is co-rotated with respect to the spin of substructure due to the assumption of kinematic hardening rule in finite deformation regime. The work piece under consideration is assumed to consist of the elastic and the rigid plastic deformation zone. Then, the J2 deformation theory is facilitated to characterize the plastic deformation behavior under various loading conditions. The plastic deformation localization behaviors strongly depend on the constitutive description namely back stress evolution and its hardening parameters. Then, the analysis for Swift's effects under the fixed boundaries in axial directions is carried out using simple shear deformation.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.777-779
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• 2001

In this study, we have estimated the brushless DC motor parameters by means of back-emf measurement and step input test. The validity of proposed parameter estimation method is confirmed by step res pons experiment. And the reasonable digital controller is designed with the root locus method of motor transfer function and revised Ziegler-Nichols gain determination method. The system stability is experimentally verified by the frequency domain analysis used Bode plot.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.195-195
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• 1999

This paper is Proposed a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nickels method. So we can find the parameters of PID controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of PID controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of PID controller is found by Neural-Network Program.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2584-2586
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• 2000

A drum level control is one of the most important control systems in thermal power plant. The control objective of drum level of boiler in thermal power plant is to maintain drum level at constant set-point regardless of disturbance such as main steam flow. The implemented drum level controller is the cascade PI controller. The important factor in drum level controller is the parameters of two PI controllers. The tuning of PI controller parameter is tedious and time-consuming job. In this paper, the relay feedback Ziegler - Nichols tuning method extended to auto-tune cascade PI drum level controller. Finally, the simulation result using boiler model in Power Plant shows the validity of auto-tuned cascade PI controller.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1110-1112
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• 1996

In this paper, we propose a new approach for robust auto-tuning of PID gains using Evolution Strategy. Evolution Strategy is searching algorithm which imitate the principles of natural evolution as a method to solve parameter optimization problem and easy to use without any other special mathematical theory. Through the simulation of the speed control of a series-connected de motor, our proposed method shows more improved performance by finding optimal parameters of PID controller than a classical Ziegler-Nichols method.

• 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 Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.2
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• pp.63-70
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• 1999

This paper is proposed a new method to deal with the optimized auto-tuning for the Pill controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. So we can find the parameters of Pill controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of Pill controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of Pill controller is found by Neural-Network Program.rogram.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.10
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• pp.1031-1036
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• 2015

Proportional-integral-derivative (PID) controllers are widely used in industrial sites. Most tuning methods for PID controllers use an empirical and experimental approach; thus, the experience and intuition of a designer greatly affect the tuning of the controller. The representative methods include the closed-loop tuning method of Ziegler-Nichols (Z-N), the C-C tuning method, and the Internal Model Control tuning method. There has been considerable research on the tuning of PID controllers for single-input single-output systems but very little for multi-input multi-output systems. It is more difficult to design PID controllers for multi-input multi-output systems than for single-input single-output systems because there are interactive control loops that affect each other. This paper presents a tuning method for the PID controller for a two-input two-output system. The proposed method uses a real-coded genetic algorithm (RCGA) as an optimization tool, which optimizes the PID controller parameters for minimizing the given objective function. Three types of objective functions are selected for the RCGA, and each PID controller parameter is determined accordingly. The performance of the proposed method is compared with that of the Z-N method, and the validity of the proposed method is examined.