• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.22.1-22
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• 2001

In this paper we present Multiple-Channel Active Noise Control[ANC] system by employing Independent Component Analysis[ICA] and Adaptive Network Fuzzy Inference System[ANFIS]. ICA is widely used in signal processing and communication and it use prewhiting and appropriate choice of non-linearities, ICA can separate mixed signal. ANFIS controller is trained with the hybrid learning algorithm to optimize its parameters for adaptively canceling noise. This new method which minimizes a statistical dependency of mutual information(MI) in mixed low frequency noise signal and there is no need to secondary path modeling. The proposed implementations achieve more powerful and stable noise reduction than Filtered-X LMS algorithms which is needed for LTI assumption and precise secondary error

• Publications of The Korean Astronomical Society
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• v.32 no.1
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• pp.59-61
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• 2017

The AKARI 9 and 18 µm diffuse maps reveal the all-sky distribution of the interstellar medium with relatively high spatial resolution of ~6". The zodiacal light is a dominant foreground component in the mid-infrared. Thus, removal of the zodiacal light is a critical issue to study low surface brightness Galactic diffuse emission. We carried out modeling of the zodiacal light based on the Kelsall model which is constructed from the COBE data. In the previous study, only a time-varying component of the zodiacal light brightness was used for determination of the model parameters. However, there remains a residual component of the zodiacal light around the ecliptic plane even after removal with the model. Therefore, instead of using a time-varying component, we use the absolute brightness of the zodiacal light and we find that the new model can better remove the residual component. As a result, the best-fit model parameters are changed from those in the previous study. We discuss the properties of the zodiacal light based on our new result.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.1-10
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• 2013

Modeling and simulation techniques construct experimental environment considering battlefields and are able to analyze performance of components of weapon system that closely resemble reality. However, developed model has low scalability and not cared reusability because it has been used only in a limited range of domain. In this paper, we develop a verification tool to verify reusability of developed component for dynamic reconfiguration and to judge scalability of it and a management tool to control data of it effectively. In addition, dynamic reconfiguration architecture of guided weapon systems designed in the previous study has been applied to SAM(Surface to Air Missile) System Simulator, and we study effectiveness of the developed component. Thus the user can configure various guided weapon systems through simulation application of dynamic reconfiguration architecture of component.

• 한국신재생에너지학회:학술대회논문집
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• 2005.11a
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• pp.541-544
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• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane (PEM) fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cel1 system, multi-variable optimization code was adopted. Using this method the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study tan be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.579-583
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• 2011

The component based propulsion modeling and simulation of an air-breathing engine such as ramjet and scramjet is studied. The simulation model has been realized considering the characteristics of the air-breathing engine which is composed of air intake, combustor and nozzle including engine controller and fuel supply system. To estimate the engine performance and to verify the engine controller, real time based Hardware in the Loop System simulating actual environment is constructed.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.417-422
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• 2000

In this paper, an efficient fuzzy rule generation scheme for adaptive neuro-fuzzy system modeling using the Independent Component Analysis(ICA) as a preprocessing is proposed. Correlation between inputs was not considered in the conventional neuro- fuzzy modeling schemes, such that enormous number of rules and large amount of error were unavoidable. The correlation between inputs is weakened by employing ICA so that the number of rules and the amount of error are reduced. In simulation, the Box-Jenkins furnace data is used to verify the effectiveness of the proposed method.

• New & Renewable Energy
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• v.1 no.4 s.4
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• pp.43-48
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• 2005

This study presents the integrated modeling approach to simulate the proton exchange membrane [PEM] fuel cell system for vehicle application. The fuel cell system consisting of stack and balance of plant (BOP) was simulated with MATLAB/Simulink environment to estimate the maximum system power and investigate the effect of BOP component sizing on system performance and efficiency. The PEM fuel cell stack model was established by using a semi-empirical modeling. To maximize the net efficiency of fuel cell system, multi-variable optimization code was adopted. Using this method, the optimized operating values were obtained according to various system net power levels. The fuel cell model established was co-linked to AVL CRUISE, a vehicle simulation package. Through the vehicle simulation software, the fuel economy of fuel cell powered electric vehicle for two types of driving cycles was presented and compared. It is expected that this study can be effectively employed in the basic BOP component sizing and in establishing system operation map with respect to net power level of fuel cell system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1449-1454
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• 2003

For many industrial processes there are good static models used for process design and steady state operation. By using system identification techniques, it is possible to obtain black-box models with reasonable complexity that describe the system well in specific operating conditions [1]. But black-box models using inductive modeling(IM) is not suitable for model based control because they are only valid for specific operating conditions. Thus we need to use deductive modeling(DM) for a wide operating range. Furthermore, deductive modeling is several merits: First, the model is possible to be modularized. Second, we can increase and decrease the model complexity. Finally, we are able to use model for plant design. Power plant must be able to operate well at dramatic load change and consider safety and efficiency. This paper proposes a simplified nonlinear model of an industrial boiler, one of component parts of a power plant, by DM method and applies optimal control to the model.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.170.2-170
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• 2001

In this paper, the dynamic system modeling and the state sensitivity analysis of the spin-coater system for the reduction of the vibration are proposed. In the respect of modeling, the spin-coater system is composed of components of servomotor, belt, spindle, and a supported base. Each component is defined and combined modeling is derived to 3dimensional equations. Verification of modeling is verified by experimental values of actual system in the frequency domain. By direct differentiation the constraint equations with respect to kinematic design variables, such as eccentricity of spindle, moment of inertia, torsional stiffness and damping of supported base, sensitivity equations are derived to the verified state equations. Sensitivity of design variables could be used for vibration reduction and natural frequency shift in the frequency domain. Finally, dominant design variables ...

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.58-66
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• 1998

In many situations, it is very important to identify a certain unkown system, it from its input-output data. For this purpose, several system modeling algorithms have been suggested heretofore, and studies regarding the fuzzy modeling based on its nonlinearity get underway as well. Generatlly, fuzzy models have the capability of dividing input space into several subspaces, compared to linear ones. But hitherto subggested fuzzy modeling algorithms do not take into consideration the correlations between components of sample input data and address them independently of each other, which results in ineffective partition of input space. Therefore, to solve this problem, this letter proposes a new fuzzy modeling algorithm which partitions the input space more efficiently that conventional methods by taking into consideration correlations between components of sample data. As a way to use correlation and divide the input space, the method of principal component is ued. Finally, the results of computer simulation are given to demonstrate the validity of this algorithm.