• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.496-498
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• 1998

This paper presents a mathod of reducing hunting size or steady state error occurred in the output signals via regulating the PID controllers gains. The PID controllers are widely used in industrial processes. Such processes have several inherent features like continuous operation, fixed set value, and difficulty in applyirty test signals. Thus, this paper suggests fuzzy rules of reducing hunting magnitude or steady state error using output signals only. Such an intelligent tuning technique utilizes both the experts, experience and control engineers' theortical background. For two kinds of systems such as temperature or DC motors speed control, we showed the validity of proposed method in this paper.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1374-1376
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• 1996

In this paper We proposed a new method to generate fuzzy logic controllers through genetic algorithm(GA). In designing of fuzzy logic controllers encounters difficulties in the selection of optimized member-ship functions, gains and rule base, which is conventionally achieved by a tedious trial-and-error process. This paper develops genetic algorithms for automatic design of high performance fuzzy logic controllers which can overcome nonlinearities in many engineering control applications. The rule-base is coded in base-7 strings by generated from random function. Which can be presented in discrete fuzzy linguistic value, and using membership function with Gaussian curve. To verify the validity of this fuzzy logic controller it is compared with conventional fuzzy logic controller(FLC) and PID controller.

• 제어로봇시스템학회논문지
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• 제18권12호
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• pp.1101-1105
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• 2012

This study proposes a method for improvement of PD type fuzzy controller. The method includes self tuner using gradient algorithm that is one of the optimization algorithms. The proposed controller improves simple Takagi-Sugeno type FLC (Fuzzy Logic Control) system. The simple Takagi-Sugeno type FLC system changes nonlinear characteristic to linear parameters of consequent membership function. The simple FLC system could control the system by calibrating parameter of consequent membership function that changes the system response. While the determination on parameter of the simple FLC system works well only partially, the proposed method is needed to determine parameters that work for overall response. The simple FLC system doesn't predict the response characteristics. While the simple FLC system works just like proportional part of PID, our system includes derivative part to predict the next response. The proposed controller is constructed with P part and D part FLC system that characteristic parameter on system response is changed by self tuner for effective response. Since the proposed controller doesn't include integral part, it can't eliminate steady state error. So we include a gain to eliminate the steady state error.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 B
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• pp.707-710
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• 1993

In this paper, we design the high accuracy speed controller of an induction motor by the Fuzzy control algorithms, which recently is invoking the remarkable interest. In order to improve the dynamic resposes such as the steady state error, the reaching tine and the overshoot, the adjustment techniques for optimization of three scale factors are presented. Comparing with conventional PID control, the usefulness of proposed Fuzzy controller will be proved by the simulations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2114-2116
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• 2002

본 논문은 개선된 Complex 방법을 이용한 하이브리드 퍼지 PID 제어기의 최적 자동동조 알고리즘을 제안한다. 제어응답은 퍼지제어기의 환산계수 값에 의해 여러 종류, 여러 형태로 변화하기 때문에 해당하는 제어계의 평가 기준을 만족하도록 제어 파라미터 값을 정하는 것이 중요하다. PID 파라미터 조정법에는 많은 방법이 제안되어 왔었다. 대표적인 예로서 Ziegler-Nichols, Cohen-Coon, Chien-Hrones-Reswick(CHR) 등에 의해 제안된 방법들이 있다. 본 논문에서는 개선된 Complex 방법을 이용한 강력한 자동동조 알고리즘이 하이브리드 퍼지 PID 제어기의 성능을 자동적으로 개선하기 위해 사용된다. 이 알고리즘은 하이브리드 퍼지 PID 파라미터와 환산계수를 제어출력 변화율과 제한조건에 따라 자동으로 추정한다. 지연시간을 갖는 1계, 2계 공정에 적용하고. 공정출력 기준치는 단위 입력으로 한다. 제어 결과의 성능평가를 위해 ITAE(Integral of Time multiplied by the Absolute value of Error)가 사용되며, 또한 제어기의 오버슈트도 토의된다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권2호
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• pp.113-118
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• 2010

This paper proposed an ECAM (Electronic cam) control system which has simple and general structure. The proposed cam controller adopted the linear and polynomial curve-fitting method to generates a smooth cam profile curve function. Smooth motion trajectory of master actuator guarantees the good performance of slave motion and has an important effect on the interpolation quality of ECAM. The auto-tuning PID velocity controller was applied to overcome the uncertainties in ECAM, and the gains of the controller are updated continuously to ensure the consistency of system performance under varying working conditions. The robustness of system against the varying load torque disturbances and noises is guaranteed by using the load torque disturbance observer to suppress the disturbance on master actuator. The velocity compensator was applied to compensate the degradation of performance of slave motion caused from the varying driving speed of master motion. The stability and validity of the proposed ECAM control system was verified by simulation results.

• 한국화재소방학회논문지
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• 제25권5호
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• pp.32-38
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• 2011

호버크래프트는 수륙양용으로 운용이 가능하고, 일반 보트에 비해 연비가 좋은 관계로 보트의 대체 수단 및 레저용으로 이용이 증가하는 추세이다. 아울러 우리나라도 소방서의 인명구조구급용으로의 수요가 점차 많아지고 있다. 본 논문에서는 호버크래프트의 전진과 후진을 자유롭게 하기 위해 후진 시 방향을 제어할 수 있는 후진 버켓 컴퓨터 시스템 제어기를 개발하였다. 제안한 시스템제어기의 타당성을 입증하기 위하여 Matlab으로 시뮬레이션 한 다음, 실제 소방서에 납품하는 기종에 장착하여 실증 실험을 수행하 였다. 그 결과 호버크래프트는 추진 공기의 흐름에 대하여 좌 우 및 역 추진이 용이하였으며 인명 구조시나 고속 주행시 등에서도 안정된 운용이 가능함을 확인 하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.328-330
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• 2005

Most of the water level controllers of the actual plant are PID controllers. But they have limitations in appling for tracking the set point and getting rid of disturbances, so there are some defects to apply in the actual ground even though many research works represented the resolution to solve it. In this paper, we design a fuzzy logic system (FLS) for controlling the steam generator water level in nuclear power plants. Some computer simulations reveal similar performance with the conventional PID controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.248-252
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• 2003

This paper has a control method proposed for the effective self-tuning fuzzy speed control based on neural network of the induction motor indirect vector control. The vector control of an induction motor provides the decoupled control of the rotor flux magnitude and the torque producing current to performance is desirable. But, the drive performance often degrades for the machine parameter variations and its condition give rise to coupling of flux and torque current. The fuzzy speed control of an induction motor has the robustness about machine parameter variations compared with conventional PID speed control in a way. That proved to be some waf from the true. The purpose of this paper is to improve the adaptation by offering self-turning function to fuzzy speed controller. In this paper, the adaptive mechanism of fuzzy speed control in used ANN(Artificial Neural Network) technique is applied in an IFO induction machine drive, such that the machine can follow a reference model (an ideal field oriented machine) to achieve desired speed. In this paper proved the self-turning method of fuzzy controller has the robustness about parameter variation and the wide range of adaptation by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.236-236
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• 2000

Control of Industrial processes is very difficult due to nonlinear dynamics, effect of disturbances and modeling errors. M.Morari proposed Internal Model Control(IMC) system that can be effectively applied to the systems with model uncertainties and time delays. The advantage of IMC systems is their robustness with respect to a model mismatch and disturbances. But it was difficult to apply for nonlinear systems. Adaptive Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to identify a nonlinear dynamical systems. In this paper, we propose new IMC design method using adaptive neuro-fuzzy inference system for nonlinear plant. Numerical simulation results show that proposed IMC design method has good performance than classical PID controller.