• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.502-504
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• 1998

This paper proposes the method that estimate optimally the parameters of Fuzzy-PID controller using genetic Algorithm. The controller is designed with the proposed method, and then is applied to 3-phase induction motor. Simulation results show that proposed method is more excellent then FPID and PID.

• Journal of Advanced Marine Engineering and Technology
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• 제23권4호
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• pp.583-592
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• 1999

In order to control systems which contain nonlinearities control strategies must deal with the effects of them. Since most of control methods based on system mathematical models have been mainly developed focused on stability robustness against nonlinearities or uncertainties under the assumption that controlled systems are linear time invariant they have certain amount of limita-tions to smartly improve control perfomances of systems disturbed by nonlinearities or uncertainties. In this paper the fuzzy PID control law is suggested which can improve control performances of the nonlinear heavy load hydraulic systems disturbed by nonlinearities and uncertainties. Although the derivation process is based on the design process similar to general fuzzy logic con-troller resultant control law has analytical forms with time varying PID gains rather than linguis-tic forms so that implementation using commn-used versatile microprocessors can be achieved easily and effectively in real-time control aspect.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.444-451
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• 2007

In this paper, we propose an improved reduction model and a reduction model-based hybrid smith-predictor fuzzy controller. The transient and steady-state responsed of the reduction model was evaluated. In tuning the controller, the parameters of PID and the factors fuzzy controllers were obtained from the reduced model and by using genetic algorithms, respectively. Simulation examples demonstrated a better performance of the proposed controller than conventional ones.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 B
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• pp.1165-1168
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권8호
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• pp.473-480
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• 2000

A fuzzy PID controller is proposed for the posture control of a two DOF robot vehicle inspecting the defects of the inner wall of sewage pipes. The main difficulty in controlling these kinds of vehicles lies in that the center of two mobile shafts does not coincide with the weight center of the vehicle due to its long and wide shape. In this case the previous controller, based on the assumption that the gap between these centers are small, can not guarantee satisfactory transient response characteristics. In this paper, this gap is included in the mathematical modelling of the robot kinematics, and in order to compensate the unsatisfactory transient response characteristics, the fuzzy PID controller is proposed. This controller tunes the PID control gains with respect to the current state of the errors between the reference and the current postures. A series of simulations has been performed to investigate the tracking performance of the proposed controller for the lane changing path and the robustness to the external disturbance. The simulation results show that the proposed controller has a satisfactory tracking performance in the transient state as compared with that of the backstepping control given in reference.

• 한국지능시스템학회논문지
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• 제13권1호
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• pp.85-90
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• 2003

본 논문에서는 퍼지모델을 이용하여 비선형 시스템을 위한 적응 PID 제어기 설계 방법을 제안한다. TSK 퍼지모델을 이용하여 제어 입력의 오차를 예측하고 그 오차로부터 PID제어기의 파라미터를 적응시킨다. TSK 퍼지모델 또한 플랜트의 실제 출력과 모델 출력을 비교하여 모델 파라미터의 적응이 가능하도록 하였다. 제안된 방법으로 비선형의 플랜트에 대한 모호성, 파라미터의 변화 등에 적응할 수 있는 PID 제어기의 설계가 가능하였다. 그리고 몇 개의 비선형 시스템에 대한 시뮬레이션으로 제안된 알고리즘의 유용성도 확인되었다.

• Journal of Electrical Engineering and Technology
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• 제7권5호
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• pp.724-729
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• 2012

A fuzzy PID controller design method is proposed for precise robust control of DC-DC buck converters. The PID parameters are determined reflecting on the common control engineering knowledge that transient performances can be improved if the P and I gains are big and the D gain is small at the beginning. Different from the previous fuzzy control design methods, the proposed method requires no defuzzification module and the global stability of the proposed fuzzy control system can be guaranteed. The proposed fuzzy PID controller is implemented by using a low-cost 8-bit microcontroller, and simulation and experimental results are given to demonstrate the effectiveness of the proposed method.

• 한국정밀공학회지
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• 제15권9호
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• pp.56-67
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• 1998

This paper introduces a friction compensation fuzzy logic controller, which utilizes a rule-based approach. The paper explains the algorithm of the proposed controller and compares it with a conventional PID controller in simulations and experiments. For the experiments, the two control algorithms were implemented on a 3-axis milling machine in contour milling. These simulation and experimental analyses show that the proposed fuzzy logic controller has superior performance over conventional PID controllers In terms of part contour accuracy.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.859-861
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• 1999

This paper describes the development of a fuzzy gain scheduling scheme of PID controller for inverted pendulum system. Fuzzy rules and reasoning are utilized on-line to determine the controller parameters based on the error signal and its difference. Simulation results demonstrate that better control performance can be achieved in comparison with PID controller using pole placement to control of a Inverted pendulum.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.531-533
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• 1998

This paper proposes the method that estimate optimally the parameters of Fuzzy-PID controller using genetic Algorithm. The controller is desined with the proposed method, and then is applied to 3-phase induction motor. Simulation results show that proposed method is more excellent then FPID and PID.