• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.699-702
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• 1991

A servo system requires faster and more accurate dynamic responses. Generally a PD control is mainly used to obtain the precision, and in the other hand a fuzzy control to improve the transient response and to cope with the nonlinearity of systems. Recently hybrid control, which is attempted to combine the advantages of PD control and a Fuzzy control was proposed, but this technique requires complicate design procedures. Therefore in this paper, a Fuzzy controller with a series of membership functions, and various sampling periods and rules, was designed on the basis of Lyapunov stability theory and auto tuning methods of input scale factors. And also it was showed to have the excellent adaptive performances against internal-external disturbances and the usefulness of this controller from the results of simulations.

• Journal of the Korean Society of Safety
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• v.12 no.2
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• pp.80-86
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• 1997

In this paper, a temperature controller with monitor function is proposed for the electric furnace system. This controller includes holding and ramp control function, and the control program for the temperature process monitor of the electric furnace. For this purpose, the implementation and performance of auto tuning algorithms in a computer-based controller was studied in relation to the control of nonlinear electric furnace system which is characterized with large delay time. The control program for this controller programmed by c-language. To communicate a control and detection signals, between the controller and the electric furnace is implemented by the I/O data card. We apply the temperature controller to the practical electric furnace. As a result, the proposed controller shows the better status characteristic.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.2
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• pp.118-123
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• 2002

A torque transmission system, which is composed of serveral gears and couplings, is flexible. Therefore, the torsion vibration occurs when the motor speed abruptly changes. Consequently, for accuracy characteristic response of motor, we must suppressed vibration. Therefore, vibration suppression is very important motor control. In order to suppress the vibration, various control method have been proposed. Specially, one method of vibration suppression is used disturbance observer and filter. The disturbance observer is used to suppress the vibration in this method. By feedback of the estimated torsion torque, the vibration can be suppressed. The coefficient diagram method is used to design the filter and proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. In order to solve this problem. we used fuzzy controller for auto tuning controller parameter $K_P$. We proved of this approach is confirmed by simulation. 

• Journal of the Korea Society for Simulation
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• v.29 no.3
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• pp.9-18
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• 2020

The development of a large-scale thermal power plant control simulator consists of water/steam systems, air/combustion systems, pulverizer systems and turbine/generator systems. Modeling is possible for all systems except mechanical turbines/generators. Currently, there have been attempts to develop neural network simulators for some systems of a boiler, but the development of simulator for the whole system has never been completed. In particular, autoTuning, one of the key technology developments of all power generation companies, is a technology that can be achieved only when modeling for all systems with high accuracy is completed. The simulation results show accuracy of 95 to 99% or more of the actual boiler system, so if the field PID controller is fitted to this simulator, it will be available for fault diagnosis or auto-tuning.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.16-21
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• 2000

In this paper we design a GA-fuzzy controller for position control and anti-swing at the destination point. Applied genetic algorithm is used to complement the demerit such as the difficulty of the component selection of fuzzy controller namely scaling factor membership function and control rules. lagrange equation is used to represent the motion equation of trolley and load in order to obtain mathematical modelling. Simulation results show that the proposed control technique is superior to a conventional optimal control in destination point moving and modification.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.239-244
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• 2002

Even though, tanks are used at the many industry plants, it is very difficult to control the tank level without any overflow and shortage; moreover, cause of its complication of dynamics and nonlinearity, it's impossible to realize the accurate control using the mathematical model which can be applied to the various operation modes. However, the sliding mode controller(SMC) is known as having the robust variable structures for the nonlinear control systems with the parametric perturbations and with the sudden disturbances, but the auto-tuning of parameters was a problem. Therefore, in this paper, a Genetic Algorithm based Sliding Mode Controller (GA-SMC) for the precise control of the coupled tank level was tried. GA optimized the SMCs switching parameters easily and rapidly. The simulation results are shown that the tank level could be satisfactorily controlled with less overshoot and steady-stale error by the proposed GA-SMC.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.8
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• pp.68-74
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• 1998

The neural network predictiv econtroller (NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output (NNP:neural network predictor) and the other one is for control the plant(NNC: neural network controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and predictin error. The NNP forecasts the future output based upon the current control input and the estimated control output. The input and the output data of a system and a new method using evolution strategy are used to train the NNP. A two-step NNPC is applied to control the temeprature in boiler systems. It was compared with PI controller and auto-tuning PID controller. The computer simulaton and experimental results show that the proposed method has better performances than the other method.

• Journal of Korean Port Research
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• v.12 no.2
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• pp.217-224
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• 1998

During the operation of crane system in container yard, the objective is to transport the load to a goal position as quick as possible without rope oscillation. The container crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. Therefore, we developed an optimal controller which has to control the crane system with disturbances. In this paper, we present a design of optima 2-DOF PID controller for the control of gantry crane which has to control swing motion and trolley position. We used evolution strategy(ES) to tune the parameters of 2-DOF PID controller. It was compared with general PID controller. The computer simulations show that the proposed method has better performances than the other method.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.43-52
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• 2022

Design of a controller for a high-precision servo control system has been a popular topic while finding optimal parameters for multiple controllers is still a challenging subject. In this paper, we propose a practical scheme to optimize multi-parameters for the robust servo controller design by introducing a new cost function and optimization scheme. The proposed design method provides a simple and practical tool for the systematic servo design to reduce the control error with guaranteeing robust stability of the overall system. The reduction of the position error by 24% along with a faster convergence rate is demonstrated using a typical hard disk drive servo controller with 41 parameters.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.85-91
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• 2000

This paper proposes a novel method with pseudo-on-line scheme using the optimized look-up table based on the genetic algorithm which does not use the gradient and finds the global optimum of an un-constraint optimization problem. The technique is a pseudo-on-line method that optimally estimates the parameters of fuzzy PID(FPID) controller for systems with non-linearity, using the genetic algorithm. The proposed controller(GFPID) with the auto-tuning function is applied to the on-line and real-time control of speed at 3-phase induction motor, and its computer simulation is carried out. simulation results show that the proposed methodis more excellent that conventional FPID and PID controllers.