• 대한산업공학회지
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• 제21권4호
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• pp.593-608
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• 1995

In this study two issues are considered, one is to develop a pneumatic servomechanism using a direct-connected circuit between inlet and outlet, the other is to design two kinds of advanced controllers such as fuzzy and PID controllers for a fingering system. Besides, the application of the advanced controllers to the newly proposed servomechanism is presented. The procedure of this study is composed of following 6 steps : [Step 1] Structuring of a control system; [Step 2] Development of a pneumatic circuit for the servomechanism ; [Step 3] Characteristic analysis of the valve and cylinder systems ; [Step 4] Determination of optimal parameters of the PID controller ; [Step 5] Design of a fuzzy controller and parameter tuning; and, [Step 6] Experimental analysis of fuzzy and PID controllers. Experimental results show that the newly proposed pneumatic servomechanism has good performance and, not only the performance of the fuzzy controller is better than that of the PID controller but also the fuzzy controller fits well to the control of the pneumatic servomechanism.

• 제어로봇시스템학회논문지
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• 제13권7호
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• pp.671-676
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• 2007

In this paper, a novel neuro-fuzzy controller is presented. The generic fuzzy controller is compensated by a neural network controller so that an overall control structure forms a neuro-fuzzy controller. The proposed neuro-fuzzy controller solves the difficulty of selecting optimal fuzzy rules by providing the similar effect of modifying fuzzy rules simply by changing crisp input values. The performance of the proposed controller is tested by controlling humanoid robot arms. The humanoid robot arm is analyzed and implemented. Experimental studies have shown that the performance of the proposed controller is better than that of a PID controller and of a generic fuzzy PD controller.

• 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 1995년도 하계학술대회 논문집 B
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• pp.992-994
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• 1995

FLC has a good performance for complication system or unknown model by using human linguistic method but many part control design are based on expert knowledge or trial-error method and it is difficult to prove stability and robustness of controller. In this paper we improve this problem by setting fuzzy rules by dividing phase plane of error and rate of error change by switching surface. We can guarantee the stability in nonlinear system, and also in fuzzy PID type controller the complexity of controller design is increased by increasing the number of input variables and defining more range of operation if we want performance of more specific rules, thus we need to fine the method to decrease the number of control rules used in FLC design. In this paper the algorithm is validated by simulation using conventional FLC and proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.999-1001
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• 1995

In this study, the algorithm of optimal parameter inference is proposed. At this inferring method, we tried to acquire the follow-up to reference pattern through comparing the plant output pattern with random reference pattern. As an inference method, the fuzzy theory was applied and the proposed algorithm was proved by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.457-462
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• 1991

Recently, digital techniques have been applied to servo systems of the home VCR, which result in high accuracy, high stability and a small number of parts required. The servo systems are now becoming more compex because the latest home VCRs are stringly required to have many functions. Given these circumstances, software servo concepts were introduced to the VCR servo system with microprocessor. But there are some difficulties in the conventional digital PID controller, eg. caculating the exact gains or dynamics. In this paper, we introduce FLC(Fuzzy Logic Controller) to the speed/phase control for VCR drum motor. To show the usefulness of the proposed controller, some studies are discussed by simulation and experiment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.129-134
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• 1992

Fuzzy theory has shown good control performance for non-linear system that is difficult to be controlled by the conventional controller. Backpropagation neural network can interpolate output without the priori knowledge of its dynamics. In this paper, we proposes a Fuzzy-Neural Controller. The Fuzzy Control by deterministic rule may not be sensitive for uncertain conditions and has a disadvantage of setting the rule by repeatedly experience. To solve such problems, we construct Self organizing Fuzzy-Neural Controller which can reorganize the fuzzy rule according to the state of system. Experimental results show that proposed Fuzzy-Neural Controller has better performance than conventional controller(PID) has especially rising time and overshoot characteristics.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권2호
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• pp.48-54
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• 2002

In this study, a neuro-fuzzy controller which has the characteristic of fuzzy control and artificial neural network is designed. A fuzzy rule to be applied is automatically selected by the allocated neurons. The neurons correspond to fuzzy rules are created by an expert. To adapt the more precise model is implemented by error back-propagation learning algorithm to adjust the link-weight of fuzzy membership function in the neuro-fuzzy controller. The more classified fuzzy rule is used to include the property of dual mode method. In order to verify the effectiveness of the proposed algorithm designed above, an operating characteristic of a DC servo motor with variable load is investigated.

• 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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 춘계학술대회 논문집
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• pp.173-177
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• 1992

The Helicopter has a lot of flight modes. The most characteristic flight mode is Hovering. It enables the helicopter to be used in many situations. However, a helicopter has nonlinear dynamics so its mathematical modeling is very difficult. Hence it is not easy to control helicopter in hover. In this paper, RC model helicopter is selected as a plant. To stabilize the behavior of RC model helicopter, Fuzzy alogrithm is used as a controller and one camera is used as a sensor. To get proper Information from camera Image, three characteristic points are attatched to the helicopter and a position recognition algorithm is developed. Experiments are performed to stabilize 3 rotational motions synchronousely with fuzzy control algorithm. As a result, Fuzzy control represents better performances than the conventional PID control.