• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.120-123
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• 1997

In this paper, we propose the Fuzzy Inference-based Reinforcement Learning Algorithm. We offer more similar learning scheme to the psychological learning of the higher animal's including human, by using Fuzzy Inference in Reinforcement Learning. The proposed method follows the way linguistic and conceptional expression have an effect on human's behavior by reasoning reinforcement based on fuzzy rule. The intervals of fuzzy membership functions are found optimally by genetic algorithms. And using Recurrent state is considered to make an action in dynamical environment. We show the validity of the proposed learning algorithm by applying to the inverted pendulum control problem.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.235-240
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.210-215
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• 1999

In this paper, a new approach to the dynamic control technique for track vehicle system using fuzzy-neural network control technique is proposed. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.205-209
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• 1998

A synthesis of fuzzy variable structure control is proposed to design a high-angle-of-attack flight system for a modification version of the F-18 aircraft. The knowledge of the proportional, integral, and derivative control is combined into the fuzzy control that addresses both the highly nonlinear aerodynamic characteristics of elevators and the control limit of thrust vectoring nozzles. A simple gain scheduling method with multi-layered fuzzy rules is adopted to obtain an appropriate blend of elevator and thrust vectoring commands in the wide operating range. Improving the computational efficiency, an accelerated kernel for on-line fuzzy reasoning is also proposed. The resulting control system achieves the good flying quantities during a high-angle-of- attack excursion. Thus the fuzzy logic can afford the control engineer a flexible means of deriving effective control laws in the nonlinear flight regime.

• Journal of the Korean Society of Marine Environment & Safety
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• v.2 no.1
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• pp.89-95
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• 1996

This paper describes a fuzzy controlled pre-chlorination technique for purifying the pulluted raw water in water purification lants. For the purpose of obtaining the high quality water, the appropriate pre-chlorine dosage rate has to be continuously adjusted according to a change in quality of a intake raw water, weather, solar nergy mount, temperature and etc. Therefore, the method of expressing an expert's empirical knowledge cumulated from his past carrier by fuzzy reasoning and the fuzzy controller design technique is necessary.In this paper fuzzy membership functions and rules accordingto emprircal knowledge and experimental field data were obtained, And also fuzzy cintriller design using four feedforward components for the determination of pre-chlorine dosage rate and four feedback ones for the compensation of its dosage rate with residual chlorine and its change rate, was executed.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1009-1011
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• 1996

This paper presents an approach to building multi-input and single-output fuzzy models for nonlinear data-based systems. Such a model is composed of fuzzy rules, and its output is inferred by simplified reasoning. Optimal structure and membership parameters for a fuzzy model are automatically and simultaneously identified by GA(Genetic Algorithm). Numerical examples are provided to evaluate the feasibility of the proposed approach. Comparison shows that the suggested approach can produce a fuzzy model with higher accuracy and a smaller number of fuzzy rules than the ones achieved previously in other methods.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.69-76
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• 2003

In this paper, a novel speed control system that implements the fuzzy logic controller(FLC) is proposed. Fuzzy controller is shown more excellent efficency than a conventional controllers in the strength aspect and non-linear controller using IF-THEN rule which can control without process the accurate mathematical modeling about induction motor. But we cannot expect that conventional fuzzy controller divide equally the space of input and output parameter and use the certain shape of triangle membership function. Therefore to develop the efficiency of conventional fuzzy controller, We need to scale the range of membership functions. In this study, proposed fuzzy controller has the ability controlling scale of membership functions using by output scaling factor.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.113-120
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• 1994

The dynamic characteristics of turning processes are complex, non-linear and time-varying. Consequently, the conventional techniques based on crisp mathematical model may not guarantee cutting force regulation. This paper presents a fuzzy controller which can regulate cutting force in turning process under varying cutting conditions. The fuzzy control rules are extablished from operator experience and expert knowledge about the process dynamics. Regulation which increases productivity and tool life is achieved by adjusting feedrate according to the variation of cutting conditions. The performance of the proposed controller is evaluated by cutting experiments in the converted conventional lathe. The results of experiments show that the proposed fuzzy controller has a good cutting force regulation capability in spite of the variation of cutting conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.117-127
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• 1995

In this paper, we suggest a motion analysis method using ART-I1 competitive learning neural network and fuzzy reasoning by matching the same objects through the consecutive image sequence. we use the size and mean intensity of the region obtained from image segmentation for the region matching by the region and use a ART-I1 competitive learning neural network wh~ch has a learning ability to reflect the topology of the input patterns in order to select characteristic points to describe the shape of a region. Motion vectors for each regions are obtained by matching selected characteristic points. However, the two dimensional image, the projection of the the three dimensional real world, produces fuzziness in motion analysis due to its incompleteness by nature and the error from image segmentation used for extracting information about objects. Therefore, the belief degrees for each regions are calculated using fuzzy reasoning to l-nanipulate uncertainty in motion estimation.

• Tunnel and Underground Space
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• v.19 no.5
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• pp.463-472
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• 2009

Many old domestic mines were excavated with the room and pillar method or the sublevel caving method and they involve the great possibility of surface subsidence, especially in the shallow depth mines. In most of these cases, the mine roadways and openings are very irregular in shape and the information about the local geology is uncertain. Consequently it is not simple to standardize the estimation method for the possibility of subsidence, especially the sinkhole subsidence. In this study, the fuzzy reasoning method has been applied for development of estimating the possibility of subsidence occurrence in abandoned mine area. This method has the advantage in producing the reliable estimation results with a simple performance procedure even when the precise information on the local geology and mining conditions is rare. For the verification of applicability of this method, the developed method has been applied to Kumho mine in Bonghwa, Kyungbook province and the Choong-ju mine in Iryu, Choongbook province where the surface subsidence occurred already.