• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.192-197
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• 2007

This paper presents Hybrid PI controller of IPMSM drive using fuzzy adaptive mechanism(FAM) control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid PI controller proposes a new method based self tuning PI controller. Hybrid PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.8
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• pp.1246-1253
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• 2009

This paper presents derived a calculating form of fuzzy inference, based on decomposition of $\alpha$-level sets. Based on the calculating form it is propose that fuzzy logic circuits of PI+PD controller are a body from fuzzy inference to defuzzificaion in cases where the command variable u directly is generated PWM. The effect of quantization on $\alpha$-levels is investigated. with input/out characteristics of fuzzy controller by simulation. It is concluded that 4 quantization levels are sufficient result for fuzzy control performance of DC servo system. Simulation and experimental results demonstrated that the hardware implementation of the proposed controller can successfully provide good performance on the position control of DC servo system.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.131-136
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• 2017

In this study, we design a controller that regulates the water leveling system which suffers from the disturbance. A number of control techniques have been reported which can reduce the amplitude of disturbance. But due to input-delay, these methods do not perform as expected. To overcome the problem, this paper introduces a filter and proposes a proportional and integral (PI) controller that combined with the filter (modifed PI controller). Moreover, we combine the controller with disturbance observer (DOB) that can estimate and eliminate disturbance. The proposed controller and combined the controller with DOB are tested using MATLAB.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.14-21
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• 2007

Sight Stabilization system is the control system to preserve Line of Sight for the targets though many nonlinear disturbances and vibrations are generated. In this paper, we identified Stabilization system using RLS algorithm, one of the system identification algorithm and found out the modeling of system. Considering nonlinear operational condition this paper proposes two Knowledge-base controllers - Fuzzy controller, Fuzzy PI Gain Scheduling controller, and simulates the performances of proposed controllers compare with Lead PI controller being used in Sight system of NFIV.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.140-142
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• 2005

본 논문은 산업용 전동기 시스템의 속도제어기에서 계단(Step)입력에 대한 속도의 오버슈트를 억제하는 새로운 방식의 반와인드업(Anti-windup)기법을 소개한다. 비례(P)제어기에서 비례적분(PI)제어기로의 전환 시점에 적분기가 적절한 초기값을 가지게 하여 오버슈트를 상쇄 시키고 빠른 응답 시간을 가지게 하였다. 시뮬레이션을 통하여 제안된 방법의 타당성을 확인하고 기존의 반와인드업 기법과 비교하여 그 우수성을 검증하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1176-1181
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• 2007

In this paper, we consider one of robust control system, fuzzy PI+fuzzy D controller dealing with noise, load, changed parameters of plant. We apply PI+D controller with a design for output of differential function and, we plan fuzzy controller with input for PID parameter of PI+D controller so We design control system meet with the change of environment with robust in relation to change of parameter. Fuzzy control is possessed of easy 4 rules and membership function and We design fuzzy PI+fuzzy D controller. Plant of this paper make a choice of 3 phase induction motor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.920-923
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• 2009

본 논문에서는 디커플링 제어를 적용함으로써 간략화된 모터 모델의 파리미터 변화에 대해 최대의 안정성을 가진 PI 제어기를 제안한다. PI 제어기 이득은 시행착오에 의해 각 요소를 줄임으로써 모터 파라미터로부터 직접 획득되며, 카리토노브 방정식은 모터 파라미터에서의 이득 변화를 평가하기 위해 사용되었다. 시스템 극점이 같은 위치에 존재하기 때문에 본 논문에서 제안하는 방법은 빠른 응답을 제공한다.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.522-523
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• 2010

BLDC 모터의 속도제어기로 주로 사용되는 PI제어기의 응답성능을 개선하기 위하여 본 논문에서는 PI-P구조를 가지는 새로운 속도 제어기를 제안한다. 제안된 방법은 PI 제어기의 출력과 시스템의 출력의 차에 P 이득을 추가하는 방법이다. 추가된 P 이득으로 인해 기존의 제어기에서 발생되는 오버슈트와 느린 정착시간을 개선 할 수 있다. 제안된 방법의 성능을 확인하기 위해서 Matlab Silmulink를 이용한 모의실험을 통해 제안된 제어기의 유용성를 확인한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.10
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• pp.992-997
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• 2010

The Propulsion Control Module(PCM) of Hall-thruster Propulsion System(HPS) for Science and Technology Satellite-3 (STSAT-3) has the flow control accuracy of less than ${\pm}$3% and the pressure control accuracy of less than ${\pm}$5%. The pressure controller adjusts pressure around the set point by using a Proportional Flow Control Valve (PFCV) and a high pressure transducer, while the flow controller regulates the flow rate using PFCV and the anode current telemetry of the Hall Thruster. The controllers are chosen as the Proportional and Integral(PI) type, and the PI gains are tuned based on the Matlab simulations. The result of the PCM test had the flow control accuracy of less than ${\pm}$1.87% and the pressure control accuracy of less than ${\pm}$5%. This paper describes the design, realization, and performance test results of the PCM.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.10
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• pp.59-68
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed high performance control of induction motor drive using multi adaptive fuzzy controller. This controller has been performed for speed control with fuzzy adaptation mechanism (FAM)-PI, current control with model reference adaptive fuzzy control(MFC) and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM-PI, MFC and ANN controller. The performance of proposed controller is evaluated by analysis for various operating conditions using parameters of induction motor drive. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.