• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.34-36
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• 2000

This paper proposes the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gain of input-output variables of fuzzy logic controller and weights of neural network using Tabu search. Neural network used to tune the output gain of FLC adaptively. We have weights of neural network learned using back propagation algorithm. We performed the nonlinear simulation on an single-machine infinite system to prove the efficiency of the proposed method. The proposed AFLC showed the better performance than PD controller in terms of the settling time and damping effect, for power system operation condition.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.160-166
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• 2005

In this paper, to overcome drawbacks of FLC a self tuning fuzzy sliding mode controller is proposed, which controls the position of excavator's attachment, which can be regarded as an ill-defined system. It is reported that fuzzy logic theory is especially useful in the control of ill-defined system. It is important in the design of a FLC to derive control rules in which the system's dynamic characteristics are taken into account. Control rules are usually established using trial and error methods. However, in the case where the dynamic characteristics vary with operating conditions, as in the operation of excavator attachment, it is difficult to find out control rules in which all the working condition parameters are considered. Experiments are carried out on a test bed which is built around a commercial Hyundai HX-60W hydraulic excavator. The experimental results show that both alleviation of chattering and performance are achieved. Fuzzy rules are easily obtained by using the proposed method and good performance in the following the desired trajectory is achieved. In summary, the proposed controller is very effective control method for the position control of the excavator's attachment.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.416-419
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• 2009

The widely used control theory based design of PI family controllers fails to perform satisfactorily under-parameter variation, nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of loaming through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. The paper proposes high performance speed and current control of synchronous reluctance motor(SynRM) drive using adaptive loaming mechanism-fuzzy neural network (ALM-FNN) and fuzzy logic control(FLC) controller. The proposed controller is developed to ensure accurate speed and current control of SynRM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. Also, this paper proposes the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.451-456
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• 1991

A robust position control scheme for DC Motor is proposed based on Fuzzy Acceleration Control. Proposed control system has the similar structure that Y. Hori proposed. But the PI type acceleration controller of it is replaced by Fuzzy Logic Controller(FLC) which is known to be robust to the operating point and parameter variations. By the simulation study for a real DC Motor, we have slowed the superiority to the continuous PI acceleration controller in the view point of robustness to the operating point and parameter variations.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1886-1900
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• 2018

This paper proposes a confronting feedback control structure and controllers for positive output elementary super lift Luo converters (POESLLCs) working in discontinuous conduction mode (DCM). The POESLLC offers the merits like high voltage transfer gain, good efficiency, and minimized coil current and capacitor voltage ripples. The POESLLC working in DCM holds the value of not having right half pole zero (RHPZ) in their control to output transfer function unlike continuous conduction mode (CCM). Also the DCM bestows superlative dynamic response, eliminates the reverse recovery troubles of diode and retains the stability. The proposed control structure involves two controllers respectively to control the voltage (outer) loop and the current (inner) loop to confront the time-varying ON/OFF characteristics of variable structured systems (VSSs) like POESLLC. This study involves two different combination of feedback controllers viz. the proportional integral controller (PIC) plus sliding mode controller (SMC) and the fuzzy logic controller (FLC) plus SMC. The state space averaging modeling of POESLLC in DCM is reviewed first, then design of PIC, FLC and SMC are detailed. The performance of developed controller combinations is studied at different working states of the POESLLC system by MATLAB-Simulink implementation. Further the experimental corroboration is done through implementation of the developed controllers in PIC 16F877A processor. The prototype uses IRF250 MOSFET, IR2110 driver and UF5408 diodes. The results reassured the proficiency of designed FLC plus SMC combination over its counterpart PIC plus SMC.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.812-814
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• 1999

In this paper, we are applied the Genetic Algorithm (GA) to design of fuzzy logic controller (FLC) for a DC Servo-Motor Speed Control. GA is used to design of the membership functions and scaling factor of FLC. To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC servo-motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.87-92
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• 1997

본 논문은 저비용이면서 정확한 제어를 수행하는 새로운 퍼지 제어기의 VHDL 설계 및 시뮬레이션을 다룬다. 제안한 퍼지 제어기 (Fuzzy Logic Controller : FLC)의 정확한 비퍼지화 연산시 소속값뿐 아니라 소속 함수의 폭을 고려함으로서 ？어진다. 제안한 퍼지 제어기 저비용성은 기존의 FLC를 다음과 같이 개조함으로서 이루어진다. 먼저, MAX-MIN 추론이 레지스터 파일의 형태로 쉽게 구현 가능한 read-modify-write 연산에 의해 대치된다. 두 번째, COG 비퍼지화기에서 요구하는 제산 연산을 모멘트 균형점의 탐색에 의해 피할 수 있다. 제안한 COG 퍼지화기는 곱셈기가 부가적으로 요구되며 모멘트 균형점의 탐색 시간이 오래 걸리는 단점이 있다. 부가적 곱셈기 요구에 의한 하드웨어 복잡도 증가 문제는 곱셈기를 확률론적 AND 연산에 의해 해결할 수 있고, 오랜 탐색 시간 문제는 coarse-to fine 탐색 알고리즘에 의해 크게 경감될 수 있다. 제안한 퍼지 제어기의 각 모듈은 VHDL에 의해 구조적 수준 및 행위적 수준에서 기술되고, 이들이 제대로 동작하는지 여부를 SYNOPSYS사의 VHDL 시뮬레이션 상에서 트럭 후진 주차 문제에 적용하여 검증하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.87-100
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• 1995

In order to control systems which contain nonlinearities of uncertainties, 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 limitations to smartly improve the transient responses of systems disturbed by nonlinearities or uncertainties. In this paper, a nonlinear fuzzy PID control method is suggested which can stably improve the transient responses of systems disturbed by nonlinearities, as well as systems whose mathematical characteristics are not perfectly known. Although the derivation process is based on the design process similar to general fuzzy logic controller, resultant control law has analytical forms with time varying PID gains rather than linguistic forms, so that implementation using common-used versatile microprocessors cna be achieved easily and effectively in real-time control aspect.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.931-940
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• 2001

In this paper, I propose Fuzzy Policing Mechanism(FPM) over ATM networks for the control of traffic which is unpredictable and bursty source. The FPM is consist of counter, subtracter and Fuzzy Logic Controller(FLC). The FLC is divided to fuzzifier, inference engine and defuzzifer The output of FLC inputs to the subtractor and it controls the counter. The counter works as a switch in transmission of cells. In simulation, I compared the FPM with the Leaky Bucket algorithm(LBM) in cell loss probability and performance characteristics. As a result, FPM gives lower cell loss probability than that of LBM and has good response behavior The FPM efficiently controls the transmission of packets which are variable traffic source and, it also has good selectivity.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.650-652
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.