• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.335-339
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• 2000

In the weaving process, tension control of the warp is important. The variation of the warp tension cause irregularities of the weft density and low quality of the woven fabrics. Due to the fact that the warp tension varies in depending on the difference between take-up velocity and let-off velocity, it is necessary to regulate the velocity of let-off in relation to that of take-up for keeping the warp tension. Futhermore, the diameter of warp beam changes in the weaving process. The changing diameter of warp beam cause changing inertia of warp beam and the velocity of the let-off. It makes the control of such a system more complex. In this paper, we propose a fuzzy controller for the warp tension control. From the computer simulation, it was observed that a developed fuzzy controller has a better performance than that of conventional PI controller.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.4
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• pp.88-94
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• 2003

The DC motor has the strong characteristics in the speed response, the system parameter variations and the external influence and is used as the speed controller with its good starting torque in the distributing industry. However development of the Microprocessor which is for high speed switching program can make better control system. This paper introduce to design of the high-effective DC motor controller that is using Software Bang-Bang Program of Fuzzy algorithm and to verity a PI controller and a Fuzzy controller.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2158-2160
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• 2002

In this paper, we designed the adaptive fuzzy controller(AFLC) using neural network and tabu search. We tuned the weights of neural network changing adaptively input/output gain of fuzzy logic controller and the gain of fuzzy logic controller using tabu search. To evaluate the proposed method's effectiveness, we apply the proposed AFLC to the speed control of an actual AC servomotor system. The experimental results show that AFLC has the better control performance than PI controller in terms of settling time, rising time and overshoot.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.315-318
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• 2008

In this paper proposed the solar tracking system to use a fuzzy control order to increase an output of the PV(Photovoltaic) array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. Recently, artificial intelligent control of the fuzzy control, neural-network and genetic algorithm etc. have been studied. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. Hence the fuzzy control was used to perform the tracking system after comparing with error values of setting-up, nonlinear altitude and azimuth. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.51-54
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• 2000

In variable structure control algorithm, sliding mode makes the closed loop system insensitive to modelling uncertainties and external disturbances. However due to imperfections in switching, the system trajectory chatters, which is very undesirable. And the insensitivity property of a sliding mode controller is present only when the system is in the sliding mode. To overcome these shortcomings, in this paper, new sliding mode control algorithm using time-varying sliding surface and fuzzy PI structrue is proposed.

• Journal of Power Electronics
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• v.11 no.4
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• pp.393-400
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• 2011

The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.144-147
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• 2006

A proportional intergral (PI) control strategy is commonly used for constant current and extinction angle control in a HVDC (High Voltage Direct Current) system. A PI control strategy is based on a stactic design where the gains of a PI controller are fixed. Since the response of a HVDC plant dynamically changes with variations in the operation point a PI controller performance is far from optimum. The contribution of this paper is the presentation of the design of a rough set based, fuzzy adaptive control scheme. Experimental results that compare the performance of the adaptive control and PI control schemes are also given.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.838-840
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• 1997

This presents a design method for fuzzy logic controllers of TCSC using genetic algorithm. Fuzzy logic controllers are applied to damp the dynamic disturbances sum as sudden changes of AC system loads. The dynamic performances of fuzzy logic controllers are compared with those of PI controllers. The simulation results show that dynamic performances of fuzzy controllers have better response than those of PI controllers when the AC system load changes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1405-1411
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• 2007

In this paper, a new speed sensorless control based on a fuzzy compensator are proposed for the interior permanent magnet synchronous motor (IPMSM) drives. The conventional proportional plus integrate(PI) control are very sensitive to step change of the command speed, parameter variations and load disturbance. To cope with these problems of the PI control, the estimated speeds are compensated by using the fuzzy logic controller (FLC). In the FLC used by the speed compensator of the IPMSM, the system control parameters are adjusted by the fuzzy rule based system, which is a logical model of the human behavior for process control. The effectiveness of algorithm is confirmed by the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.307-311
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• 2003

2-mass system is generally used as controller of the variable-speed to transfer electromotion power to mechanical load such as industrial robot, driving parts of electric vehicle, rolling machine system of steel plant and driving parts of elevator. In this case, PI controller is often used as a velocity controller because of simplicity of system. But PI control algorithm is not enough for obtaining the control characteristics required for this system. To solve this problem, 2-mass system based on the PID controller derives the optimum PID parameters by pole assignment and estimation of the ITAE performance index. In this case, the system have tenacious properties about disturbance, but it causes extreme overshoot and vibration because of rapidly output of controller in early transient response about desired value. And if speed control system is applied by 2-DOF parameter ${\alpha}$, a temporary value, we must induce most suitable parameter by complicate pole assignment and estimation of the ITAE performance index whenever ${\alpha}$ changes. In this paper, to solve this problem we suggest control algorithm to followed exactly value of ${\alpha}$ as 2-DOF parameter by using fuzzy algorithm . So, intelligence algorithm modeled by human knowledge, experience, teachability and judgment follow exact ${\alpha}$ value and it can compose the efficient 2-DOF PID controller to improve following performance, overshoot decrease.