• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.105-108
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• 2000

Many control techniques have been proposed in order to improve the control performance of discrete-time domain control system. In the position control system using a DC servo motor as a driver, the response-characteristic of system is controlled by the PID controller. In the PID control system, the transient response characteristic is more increased and settling time gets longer if gains of PID controller are unsuitable. In this paper, therefore, a expended PID control system is constructed by inserting a pre-compensator at output terminal of PID controller. It is implemented by using the double layers neural network. Form the results of computer simulation in the proposed control algorithm, its usefulness is verified.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.3
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• pp.298-305
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• 2015

This paper provides experimental results of an excitation control system of the synchronous generator on board ships in accordance with rules of classification society to make sure its performance. The experiment compares and reviews control results between PID control and fuzzy logic control applied to change of loads of the generator in order to make sure to satisfy the rules of classification society. Both of them are written by Labview program. In case of PID Control, this paper firstly adjusts the gains by ultimate sensitive method and the gains is more tuned by engineer's experience. And the fuzzy logic controller uses Mamdani method to make membership function for error between reference voltage and measuring voltage, differential error rate and output voltage. This paper is to make sure the experimental results of the proposed excitation control system applied to actual small synchronous generator with PID control and fuzzy logic written by using Labview program and it is proved on stability and improvement through experiments.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.1
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• pp.40-46
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• 1999

A self-tuning FPID(Fuzzy Proportional Intergral Derivative) controller fo load frequency control of 2-area power systemis proposed in this paper. The paramters of the proposed self-tuning FPID controller are self-tuned by the proposed fuzzy inference technique. Therefore in this paper the fuzzy inference technique of PID gains using PSGM(Product Sum Gravity Method) is presented and is applied to the load frequency control of 2-area power system. The computer simulation results show that the proposed controller give better more control characteristics than convention-al PID, FLC under load changes.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.7
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• pp.283-288
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• 1985

This paper is concerned with the analysis of microprocessor-based PID control for the current source inverter-induction motor derive system. A linearized dynamic model of the motor is derived and is converted into the discrete-time model. With the equation, the overall system including the feedback loops is formulated into a single discrete-time state equation. The stability regions are determined at various values of controller gains. The transient responses of the motor speed are simulated by digital computer and are verified by laboratory experiments.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1995.03a
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• pp.131-144
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• 1995

This paper presetns modifications of a hydraulic shovel to robotize, and we derive a dynamic model of the hydraulic shovel arms,and hydraulic analysis are discussed . Then , our purpose is making to imitate a target railroad line of the grinder position by the PID control. Moreover, to determine the gains of the PId controller, we referenced the Ziegler and Nichols' method. In this paper, we demonstrated that the PID control is available for system. These results indicated the possibility of practical use fo the deburring robot with the hydraulic shovel.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.991-997
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• 2013

In this paper, we propose a CFWC (CCD and fuzzy PID based width control) scheme to obtain the desired delivery width margin of a vertical rolling mill in hot strip process. A WMS(width measurement system) is composed of two line scan cameras, an edge detection algorithm, a glitch filter, and so on. A dynamic model of the mill is derived from a gauge meter equation in order to design the fuzzy PID controller. The controller is a self-learning structure to select the PID gains from the error and error rate of the width margin. The effectiveness of the proposed CFWC is verified from simulation results under a width disturbance of the entry in the mill. Using a field test, we show that the performance of the width control is improved by the proposed control scheme.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2470-2472
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• 2001

This paper describes the application of a fuzzy-tuning PID controller to a 3-DOF attitude control of a small model helicopter in hover for the compensation of coupling effects between each axis and system uncertainties due to the variation of engine RPM. A Low-level PID controller is designed by Ziegler-Nichols method and its gains are tuned by a high-level fuzzy system based on error states and its time derivatives. The experimental results show that the attitude control performance of fuzzy-tuning PID controller is improved comparing with that of a Ziegler-Nichols PID controller and fuzzy 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.

• Journal of Biosystems Engineering
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• v.31 no.3 s.116
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• pp.203-208
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• 2006

This study was conducted to improve the control performance of a current variable-rate controller for granular fertilizers. Simulation model was developed. Optimized proportional, integral and derivative gains were determined by simulation model using 2nd order PID gain learning algorithm, and these control gains were evaluated through the field tests. Important results of this study are as follows; 1. Principles of pre-existing variable-rate application of granular fertilizers were investigated. 2. Simulation model of a PID controller that could simulate the control system was developed by using Matlab/Simulink program. The program was to determine PID control coefficients through the simulation model and 2nd order PID gain learning algorithm. 3. PID control coefficients obtained from the simulation were applied to the developed model. When the step input was given, Maximum overshoot were 1.96%, rise time were 0.05 sec, settling time were 0.06 sec and steady state error were 0.21 % respectively. 4. The simulation model was verified through field tests. The errors of maximum overshoot were 10%, rise time were 0.11 sec, settling time were 0.40 sec and steady state error were 8% because of loads and noises. Rise time was decreased to one third of that of the pre-existing system. 5. If the speed of a fertilizing machine is $0.3{\sim}0.6\;m/s$ and the maximum rotation speed of a discharging roller is 64 rpm, rise time would be 0.26 sec and fertilizing machine would cover the distance of $0.07{\sim}0.15\;m$ with settling time of 0.4 sec, fertilizing machine would cover the distance of $0.12{\sim}0.24\;m$.