• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.7
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• pp.475-483
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• 1988

One of the advantages of the well-known PID controller is that it is a sufficiently flexible controller for many applications. But, when the plant parameters and disturbances are unknown or change with time, it is desirable to make automatic tuning of PID controller in order to achieve an acceptable level of performance of the control system. This paper presents a reformulation of the self-tuning pole-zero placement controller subject to some conditions and restrictions. It has the structure of a digital PID controller and is based on Vogel and Edgar's pole-zero placement design method. Various properties of this self-tuning PID controller are described and illustrated by simulation examples.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1869-1875
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• 2008

Recently, a direct data-driven synthesis of a proportional integral derivative(PID) controller for a linear time-invariant(LTI) plant was presented in [1]. The authors showed that a complete set of PID controllers achieving robust performance and stability can be calculated directly from frequency response(FR) data without an identified transfer function model. However, it is not convenient to use this method because it requires complicated numerical algorithms to find specific frequencies which are solutions of an identical equation. The method also requires determination of the boundary of the controller's parameters from a finite set of FR data. In this paper, we present the development of a user-friendly Matlab toolbox based on the method in [1]. This toolbox allows us to obtain a complete three-dimensional(3-D) graphical solution of PID controllers that meet multiple design objectives. Several examples are given to demonstrate the use of the toolbox.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.815-817
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• 1999

In the two-mass system driving a load through a flexible shaft or transmission system, a shaft torsional vibration is often generated. In this case, it's difficult to control only by conventional PI controller. To solve this problem. the two-mass speed control system with PID controller is designed by using pole assignment method, and an optimum PID parameters are derived by evaluating ITAE(Integral of time multiplied by the absolute error) performance index. Simulation results show the validity of the proposed PID controller and this controller is compared with the conventional PID controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.703-710
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• 1994

This paper describes for the applicability of optimal PID controller to the load frequency control of 2-area power systems. The proposed optimal PID controllers are designed by the optimization technique of P.I.D's gain coefficients using the relatively ingeneous simplex method, and we have considered the system sensitivity for the optimal gains and the stable effects of systems to speed regulation changes. This PID controller for load frequency control systems with exciter shows better performances and robustness than conventional tie-line bias controller.

• Membrane and Water Treatment
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• v.9 no.2
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• pp.129-136
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• 2018

In this contribution, the control of multivariable reverse osmosis (RO) desalination plant using proportional-integral-derivative (PID) controllers is presented. First, feed-forward compensators are designed using simplified decoupling method and then the PID controllers are tuned for flux (flow-rate) and conductivity (salinity). The tuning of PID controllers is accomplished by minimization of the integral of squared error (ISE). The ISEs are minimized using a recently proposed algorithm named as teacher-learner-based-optimization (TLBO). TLBO algorithm is used due to being simple and being free from algorithm-specific parameters. A comparative analysis is carried out to prove the supremacy of TLBO algorithm over other state-of-art algorithms like particle swarm optimization (PSO), artificial bee colony (ABC) and differential evolution (DE). The simulation results and comparisons show that the purposed method performs better in terms of performance and can successfully be applied for tuning of PID controllers for RO desalination plants.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.303-311
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• 2012

In this study, we introduce a dynamic process model as well as the design methodology of optimized fuzzy controller for its efficient application to vacuum production system to produce a semiconductor, solar module and display and so on. In a vacuum control field, PID control method is widely used from the viewpoint of simple structure and preferred performance. But, PID control method is very sensitive to the change of environment of control system as well as the change of control parameters. Therefore, it's difficult to get a preferred performance results from target system which has a complicated structure and lots of nonlinear factors. To solve such problem, we propose the design methodology of an optimized fuzzy PID controller through a following series of steps. First a dynamic characteristic of the target system is analyzed through a series of experiments. Second the process model is built up and its characteristic is compared with real process. Third, the optimized fuzzy PID controller is designed using genetic algorithms. Finally, the fuzzy controller is applied to target system and then its performance is compared with that of other conventional controllers(PID, PI, and Fuzzy PI controller). The performance of the proposed fuzzy controller is evaluated in terms of auto-tuned control parameters and output responses considered by ITAE index, overshoot, rise time and steady state time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.63-64
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• 2012

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.255-256
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• 2012

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.305-314
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• 2009

The purpose of this paper was to design an effective control system of 1-axis exciter for a seat vibration test of agricultural tractors using MATLAB simulation. The developed simulation model was composed with a hydraulic pump, a hydraulic servo valve, a hydraulic cylinder and load system. Also it was verified by comparing the simulation results with experimental results of actual control system in order to optimize the control performance. And in order to improve its control performance, the designed PID controller in this research was tuned using Ziegler-Nichols 2nd law and zero's moving method of PID controller's transfer function. As the result of these research, the developed position control system was able to control the system's position accurately within 5% errors.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2299-2301
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• 2000

In this paper, the design of PID controller using Neural networks for the control of non-linear system is presented. First, non-linear system is identified using BPN(Backpropagation Network) algorithm. This identified model is connected to the PID controller and the parameters of PID controller are updated to the direction of reducing the difference between the identified model output and model reference output in arbitrary input signal. Therefore, identified model output tracks the model reference output in an acceptable error range and the parameters of controller are updated adaptively. The output of the system has a good performance in case of both noisy and noiseless model reference and we can control the system stable in off-line when the dynamics of the system is changed.