• 한국지능시스템학회논문지
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• 제15권3호
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• pp.343-348
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• 2005

This paper describes an automatic finite element (FE) mesh generation for three-dimensional structures consisting of free-form surfaces. This mesh generation process consists of three subprocesses: (a) definition of geometric model, i.e. analysis model, (b) generation of nodes, and (c) generation of elements. One of commercial solid modelers is employed for three-dimensional solid structures. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Delaunay method is introduced as a basic tool for element generation. Automatic generation of FE meshes for three-dimensional solid structures holds great benefits for analyses. Practical performances of the present system are demonstrated through several mesh generations for three-dimensional complex geometry.

• 제어로봇시스템학회논문지
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• 제17권3호
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• pp.258-263
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• 2011

In the bilateral tele-operation system, time delay may be a critical problem. Even if system modeling error or time delay occurs, when applied to wave transformation system, the system's stability can be achieved. Using the characteristic b which is an important parameter of wave transformation, the system can display robust performance for time delay. However, since assuming and that the time delay was fixed developing a theory, a stability cannot be guaranteed about the time-varying delay. Therefore, In the paper, Therefore, in this paper, we studied for the method that controls this by applying the fuzzy algorithm which surveyed the timevarying delay characteristics and can adjust the b according to it adaptively.

• 한국군사과학기술학회지
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• 제3권2호
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• pp.71-80
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• 2000

In Underwater Flight Vehicle depth control system, the followings must be required. Firstly, It need robust depth control performance which can get over parameter variation, modeling error and disturbance. Secondly, It need no oveshoot phenomenon to avoid colliding with ground surface and obstables. Thirdly, It need continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, It need effective interpolation method which can reduce the dependency of control parameters on speed. To solve these problems, we propose the Fuzzy-PID depth controller with the control parameter interpolators. Simulation results show the proposed control scheme has robust and accurate performance with continuous control input.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2351-2353
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• 1998

This paper suggests the wheel controller for PWS(Power Wheeled Steering) mobile robot. The proposed controller consists of two parts. To control each motor, the sliding mode controller implemented. This method has robustness about modeling error and disturbance, so the velocity tracking is well guaranteed in the presence of varying load. The design of a fuzzy cross-coupling controller for a PWS mobile robot is described here. Fuzzy cross-coupling control directly minimizes the tracking error by coordinating the motion of the two drive wheels. The fuzzy cross-coupling controller has excellent disturbance rejection and therefore is advantageous when the robot is not loaded symmetrically. The capability of the proposed controller was verified through the computer simulation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2485-2487
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• 2000

In this paper, we use a fuzzy algorithm to detect and diagnose the error which is caused by time delay of the computer-controlled system. Generally, a computer-controlled system is composed of computer and process. And they communicate the data each other. In data communication, error occurs by some reasons, such as noise, disturbance, hardware defect, etc. Time delay is one of the reasons. And time delay makes it difficult to distinguish whether the system really has a problem or not. Therefore, we need to detect and diagnose the error from time delay. For difficulty of modeling and ambiguity of classification, we use a fuzzy algorithm. To verify the better performance of the proposed algorithm, we exemplified by some simulation results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.830-832
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• 1995

A position Control algorithm of the flexible manipulator is studied. The proposed algorithm is based on a Fuzzy Logic Control(FLC) method using the human's experiences. FLC does not need a dynamic modeling of a flexible manipulator. A Fuzzy logic controller is designed that the end-point of the flexible manipulator tracks the desired trajectory. The control input to the process is determined by the error and variation of error. Simulation result shows a robustness of FLC compared with the PID control algorithm.

• 제어로봇시스템학회논문지
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• 제13권6호
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• pp.542-546
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• 2007

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.

• 대한조선학회논문집
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• 제45권2호
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• pp.213-220
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• 2008

The aim of this paper is to build up the design model using ASMOD(Adaptive Spline Modeling of Observation Data) for the optimum scale of fleet, ship particulars and ship speed, etc. ASMOD, which define membership functions of fuzzy rule as B-spline basis function, represents a whole system as the sum of the sub-model. As it reduces the number of division of the space generated by the fuzzy set of input variables, it has a advantage of simplification to model structure and is efficient to represent the non-linear model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권2호
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• pp.108-112
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• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.1073-1075
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• 1996

This paper presents a neuro fuzzy system(NFS) for implementing fuzzy inference system with a monotonic membership function. The modeling and control of a discrete nonlinear system using a NFS is described. The membership function parameters of a identifier and controller are adjusted by back-propagation algorithm. These identifier and controller is constructed to proposed NFS. A on-line identification and control are accomplished by this NFS. A controller is gived information of the system, that is variation of the system output according to that of the control input by a identifier. A controller makes control input in order to control discrete-time nonlinear system. A Simulation is presented to demonstrate the efficiency of a suggested method.