• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.4
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• pp.195-202
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• 2002

The high performance position controller named 'Unified PID Position Controller'is presented in part 1 of this paper. In part 2, we provide smart gain adjustment methods including the freedom utilizations for rare sensitivity toward the system parameter variation and for increasing the stiffness of the system. Owing to the provided gain tuning strategy, the overall system characteristics can be stabilized without over-shoot phenomena when the system parameter is changed in the rate of from 0.5 to 2∼4. Moreover, for the actual feasibility to the industrial fields, a simple butt effective anti-windup strategy prohibiting the integral component of the PID position controller from saturation is presented too. All of the presented algorithms are verified through the experiment works with commercial linear motor.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.621-623
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• 1999

In this paper, Model following PID control system, which is combined PID controller with Model Reference Adaptive Controller, is proposed. To decrease complex and much calculation which is produced in tuning process, the tuning method of parameter with fuzzy algorithm is introduced. Fuzzy algorithm isn't used in the form of controller generally much used, but tuner. Experimental results show that proposed controller has the PID parameter be tuned by fuzzy algorithm. Therefore, We expect model following PID to be operated in the real-time control.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.87-88
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• 2006

In this paper, tuning rules of the PID controller for load disturbance rejection are proposed incorporating with real-coded genetic algorithms(RCGAs). The optimal parameters sets of the PID controller are obtained based on a first-order plus time delay model and a RCGA. As for assessing the performance of the controller, criteria(ISE, IAE and ITAE) are adopted. Then tuning formulae are derived using the tuned parameters sets, potential tuning rule models and another RCGA. A simulation work is carried out to verify the effectiveness of the proposed rules.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.6
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• pp.760-769
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• 2006

This paper proposes an autopilot system using a fuzzy PID controller to satisfy performances required for the automatic navigation of ships under various marine circumstances. The existing autopilot system using a PD type controller has difficulties in eliminating a steady-state error and compensating nonlinear characteristics of ships. The autopilot system using the proposed fuzzy PID controller has a self-tuning ability, an ability to compensate nonlinear characteristics, and an ability to turn at constant angular velocity. Therefore. it can naturally make a steady-state error zero, compensate nonlinear dynamic effect of ships, have an adaptability to parameter variation owing to shallow water effect, and have an ability to turn ship's course rapidly without overshoot through procedures of acceleration, constant, and deceleration of angular velocity for large course-changing.

• 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.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.86-88
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• 1995

This paper presents a design technique of the fuzzy PID controller for power system stabilization. PID parameters of the fuzzy PID controller was self-tuned by the fuzzy inference algorithm. The Nosed controller compare with conventional power system stabilizer(PSS) under various of initial value of rotor angle deviation and load condition. The related simulation results show that the Nosed controller was more excellent control characteristics than conventional PSS in transient-state and steady-state response.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.257-260
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• 1997

This paper designs the optimal PID controller for load frequency control on 2-area power system. Genetic algorithm is utilized to optimize parameters of PID controller which is applied to power system. Using two-point crossover, uniform crossover and one-point crossover, Search performance of genetic algorithm with each crossover method is considered. In case of load variation in 1-area, the dynamic characteristic of power system is considered. The simulation results show that the proposed PID controller is better control performance than PID controller using Ziegler-Nichols method.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.36-42
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• 1996

In this paper, we proposed a PID controller, which could control unknown plants using Artificial Neural Network(ANN) for auto-tuning of the PID parameters. In the proposed algorithm, the parameters of the controller were adjusted to reduce the error of the controlled plant. In this process, the sensitivity between input and output of the unknown plant was needed. So, in order to obtain this sensitivity, the ANN's learnig ability was used. Computer simualtions were performed for the regulation problems, and the results were compared with those of Ziegler-Nichols PID controller. As a result, it was shown that the proposed algorithm outperformed Ziegler-Nichols controller in rise time, overshoot, undershoot, and setting time.

• 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 KIPE Conference
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• 2019.07a
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• pp.115-117
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• 2019

In this paper, an intelligent control scheme based on Fuzzy PID controller is proposed for accurate power sharing in DC Microgrid. The proposed Fuzzy PID controller is designed with the aid of a closed loop control based on per unit power of each distributed generator (DG), and accurate power sharing is successfully realized in proportional to each DG's power rating regardless of the line resistance difference or the load change. Thanks to Fuzzy PID controller, the dynamic response becomes faster and the stability of the microgrid system are improved in comparison to conventional PID controller. The superiority of the proposed method is analyzed and verified by simulation in Matlab and Simulink.