• 한국정밀공학회지
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• 제19권9호
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• pp.51-58
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• 2002

Vehicle dynamics control systems are. complex and non-linear, so they have difficulties in developing a controller for the anti-lock braking systems and the auto-traction systems. Currently the fuzzy-logic technique to estimate the absolute vehicle speed is good results in normal conditions. But the estimation error in severe braking is discontented. In this paper, we estimate the absolute vehicle speed by using the wheel speed data from standard 50-tooth anti-lock braking system wheel speed sensors. Radial symmetric basis function of the neural network model is proposed to implement and estimate the absolute vehicle speed, and principal component analysis on input data is used. Ten algorithms are verified experimentally to estimate the absolute vehicle speed and one of those is perfectly shown to estimate the vehicle speed with a 4% error during a braking maneuver.

• 한국해양공학회지
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• 제8권2호
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• pp.131-140
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• 1994

Dynamics of AUV has heavy nonlinearities and many unknown parameters due to its bluff shape and low cruising speed. Intelligent algorithms, therefore, are required to overcome these nonlinearities and unknown system dynamics. Several identification techniques have been suggested for the application of control of underwater vehicles during last decade. This paper applies the neural network to identification and motion control problem of AUVs. Nonlinear dynamic systems of an AUV are identified using feedforward neural network. Simulation results show that the learned neural network can generate the motion of AUV. This paper, also, suggest an adaptive control scheme up-dates the controller weights with reference model and feedforward neural network using error back propagation.

• 한국지진공학회논문집
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• 제23권1호
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• pp.83-88
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• 2019

Structural analysis remains as an essential part of any integrated civil engineering system in today's rapidly changing computing environment. Even with enormous advancements in capabilities of computers and mobile tools, enhancing computational efficiency of algorithms is necessary to meet the changing demands for quick real time response systems. The finite element method is still the most widely used method of computational structural analysis; a robust, reliable and automated finite element structural analysis module is essential in a modern integrated structural engineering system. To be a part of an automated finite element structural analysis, an efficient adaptive mesh generation scheme based on R-H refinement for the mesh and error estimates from representative strain values at Gauss points is described. A coefficient that depends on the shape of element is used to correct overly distorted elements. Two simple case studies show the validity and computational efficiency. The scheme is appropriate for nonlinear and dynamic problems in earthquake engineering which generally require a huge number of iterative computations.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문초록집
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• pp.319.1-319
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• 2002

A frequency-domain PES estimation and its prediction method are proposed for the tightly-coupled servo/mechanical design of high-TPI HDD system above 100kTPI. The major two disturbance energies which are related with mechanical vibrations inside of HDD are used to predict the drive-level PES, while considering closed-loop servo dynamics. One is the torque disturbance which mainly comes from aerodynamic excitation of HSA system and the other is the displacement disturbance from disk-spindle dynamics. (omitted)

• 대한기계학회논문집A
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• 제25권8호
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• pp.1227-1234
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• 2001

A multi d.o.f robotic manipulator is considered for multi-axis vibration control of a slender structure, using the concept of the flow source based vibration control. In order not to cause the motion saturation of the manipulator system, a hybrid dynamics associated with the flexible and desired manipulator error dynamics is also modeled as the control object. It is numerically shown that the flexible vibrations and the base motions of a test structure can be effectively controlled with the proposed hybrid dynamics.

• Bulletin of the Korean Chemical Society
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• 제25권5호
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• pp.737-741
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• 2004

We presents new results for transport properties of dumbbell fluids by equilibrium molecular dynamics (EMD) simulations using Green-Kubo and Einstein formulas. It is evident that the interaction between dumbbell molecules is less attractive than that between spherical molecules which leads to higher diffusion and to lower friction. The calculated viscosity, however, is almost independent on the molecular elongation within statistical error bar, which is contradicted to the Stokes' law. The calculated thermal conductivity increases and then decreases as molecular elongation increases. These results of viscosity and thermal conductivity for dumbbell molecules by EMD simulations are inconsistent with the earlier results of those by non-equilibrium molecular dynamics (NEMD) simulations. The possible limitation of the Green-Kubo and Einstein formulas with regard to the calculations of viscosity and thermal conductivity for molecular fluids such as the missing rotational degree of freedom is pointed out.

• Nuclear Engineering and Technology
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• 제36권1호
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• pp.64-72
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• 2004

The purpose of this study is to develop a system dynamics model for the assessment of the organizational and human factors in a nuclear power plant which contribute to nuclear safety. Previous studies can be classified into two major approaches. One is the engineering approach using tools such as ergonomics and Probability Safety Assessment (PSA). The other is the socio-psychology approach. Both have contributed to find organizational and human factors and to present guidelines to lessen human error in plants. However, since these approaches assume that the relationship among factors is independent they do not explain the interactions among the factors or variables in Nuclear Power Plants. To overcome these restrictions, a system dynamics model, which can show cause and effect relationships among factors and quantify the organizational and human factors, has been developed. Handling variables such as the degree of leadership, the number of employees, and workload in each department, users can simulate various situations in nuclear power plant organization. Through simulation, users can get insights to improve safety in plants and to find managerial tools in both organizational and human factors.

• Journal of the korean society of oceanography
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• 제39권4호
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• pp.222-233
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• 2004

Using nitrogen as the limiting nutrient, the default version of a microplankton-detritus model linked chlorophyll concentration to the autotroph nitrogen. However, phosphorus dynamics were added to simulate the results of a microcosm experiment. Using standard parameter values with a single value of microheterotroph fraction in the microplankton taken from the observed range, the best simulation successfully captured the main features of the time-courses of chlorophyll and particulate organic carbon, nitrogen and phosphorus, with root-mean-square error equivalent to 29% of particulate concentration. A standard version of microbiological model assumes complete internal cycling of nutrient elements; adding a term for ammonium and phosphate excretion by microheterotrophs did not significantly improve predictions. Relaxing the requirement for constant microheterotroph fraction resulted in an autotroph-heterotroph model AH, with dynamics resembling those of a Lotka-Volterra predator-prey system. AH fitted the microcosm data worse than did MP, justifying the suppression of Lotka-Volterra dynamics in MP. The paper concludes with a discussion of possible reasons for the success of the simple bulk dynamics of MP in simulating microplankton behaviour.

• 대한전기학회논문지
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• 제43권5호
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• pp.838-847
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• 1994

Although there is an analytical proof of modeling capability of the neural network, the convergency error in nonlinearity modeling is inevitable, since the steepest descent based practical larning algorithms do not guarantee the convergency of modeling error. Therefore, it is difficult to apply the neural network to control system in critical environments under an on-line learning scheme. Although the convergency of modeling error of a neural network is not guatranteed in the practical learning algorithms, the convergency, or boundedness of tracking error of the control system can be achieved if a proper feedback control law is combined with the neural network model to solve the problem of modeling error. In this paper, the neural network is introduced for compensating a system uncertainty to control a nonlinear dynamic system. And for suppressing inevitable modeling error of the neural network, an iterative neural network learning control algorithm is proposed as a virtual on-line realization of the Adaptive Variable Structure Controller. The efficiency of the proposed control scheme is verified from computer simulation on dynamics control of a 2 link robot manipulator.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.122-127
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• 2002

A frequency-domain PES estimation and its prediction method are proposed for the tightly-coupled servo/mechanical design of high-TPI HDD system above 100 kTPI. The major two disturbance energies which are related with mechanical vibrations inside of HDD are used to predict the drive-level PES, while considering closed-loop servo dynamics. One is the torque disturbance which mainly comes from aerodynamic excitation of HSA system and the other is the displacement disturbance from disk-spindle dynamics. In order to obtain the accurate error transfer function of closed-loop servo control, the plant model is measured by accurate experiment. The measured PES is compared with predicted one in terms of frequency-domain PES spectrum and its standard variation value. It is proved that the proposed frequency-domain PES estimation/prediction method is capable of predicting drive-level PES of high-TPI hard disk drive.