• 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

• Structural Engineering and Mechanics
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• v.61 no.5
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• pp.675-684
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• 2017

In this paper, a hybrid seismic response control (HSRC) system was developed to control bridge behavior caused by the seismic load. It was aimed at optimum vibration control, composed of a rubber bearing of passive type and MR-damper of semi-active type. Its mathematical modeling was driven and applied to a bridge model so as to prove its validity. The bridge model was built for the experiment, a two-span bridge of 8.3 meters in length with the HSRC system put up on it. Then, inflicting the EI Centro seismic load on it, shaking table tests were carried out to confirm the system's validity. The experiments were conducted under the basic structure state (without an MR-damper applied) first, and then under the state with an MR-damper applied. It was also done under the basic structure state with a reinforced rubber bearing applied, then the passive on/off state of the HSRC system, and finally the semi-active state where the control algorithm was applied to the system. From the experiments, it was observed that pounding rather increased when the MR-damper alone was applied, and also that the application of the HSRC system effectively prevented it from occurring. That is, the experiments showed that the system successfully mitigated structural behavior by 70% against the basic structure state, and, further, when control algorithm is applied for the operation of the MR-damper, relative displacement was found to be effectively mitigated by 80%. As a result, the HSRC system was proven to be effective in mitigating responses of the two-span bridge under seismic load.

• Journal of the Korean Solar Energy Society
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• v.34 no.4
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• pp.123-129
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• 2014

Photovoltaic and fuel cell systems can be used as power source in mobile robots. At this time the photovoltaic system generally generate power in daytime. The starting time of fuel cell is slower than the lithium battery. To compensate for these disadvantages, a battery charge-discharge system is used. Especially the bi-directional converter is used mainly in the charge-discharge method. The controller in a buck converter controls the input voltage of the converter to meet the maximum power point tracking(MPPT) performance. First of all, the simulations of hybrid system for battery charge-discharge system in each step simulated using solar and fuel cell modeling as input source in PSIM. Experiment of the buck and bi-directional converter system is conducted through using photovoltaic/fuel cel simulator(pCube) instead of solar and fuel cell. This hybrid system for battery charge discharge using photovoltaic/fuel cell generates emergency power for the communication system in mobile robot.

• The Journal of Bigdata
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• v.2 no.1
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• pp.41-48
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• 2017

Recently, the popularity of the recommendation system and the evaluation of the performance of the algorithm of the recommendation system have become important. In this study, we used modeling and RMSE to verify the effectiveness of various algorithms in movie data. The data of this study is based on user-based collaborative filtering using Pearson correlation coefficient, item-based collaborative filtering using cosine correlation coefficient, and item-based collaborative filtering model using singular value decomposition. As a result of evaluating the scores with three recommendation models, we found that item-based collaborative filtering accuracy is much higher than user-based collaborative filtering, and it is found that matrix recommendation is better when using matrix decomposition.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.940-945
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• 2009

Energy planning for hybrid energy system is important to increase the flexibility in the urban community and national energy systems. Expected maximum loads, load profiles and yearly energy demands are important input parameters to plan for the technical and environmental optimal energy system for a planning area. The method for energy demand prediction has been based on artificial neural networks(ANN). The advantage of ANN with respect to the other method is their ability of modeling a multivariable problem given by the complex relationships between the variables. This method can produce 10% of errors hourly load profile from individual building to urban community. As the results of this paper, energy demand prediction system has been developed based on simulink.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.60-67
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• 2014

The battery cells in lithium-ion battery pack assembled with high-capacity and high-power pouch cells, are commonly cooled with thin aluminum cooling plates in contact with the cells. For HEV/EV lithium-ion battery systems assembled with high-capacity, high-power pouch cells, the cells are commonly cooled with thin aluminum cooling plates in contact with the cells. Thin aluminum cooling plates are cooled by cold plate with coolant flow paths. In this study, the effect of the battery cooling system design including aluminum cooling plate thickness and various position of cold plate on the cooling performance are investigated by using finite element methods (FEM). Optimal cooling plate and cold plate design are proposed for improving the uniformity in temperature distributions as well as lowering average temperature for the cells with large capacities based on the simulation results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.273-277
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• 1995

Many hudraulic components have nonlinearities to some extent. These nonlinearities often cause the time delay, thus degrading the performance of the hydraulic control systems and making it difficult to modelthem. In this paper, a new vibration isolation control algorithm that eliminates the necessity of a sophiscated modeling of hydraulic system was proposed. The algotithm is a hybrid type control shecheme consisting of a linear controller and a hetero-synaptic neural network controller. Using this control scheme, simulations and experiments were performed for 1 DOF(Degree of freedom) and 2 DOF vibration isolation. The hybrid type control algorithm can isolate the base vibration signifcantly rather than linear control algorithm. And from the weights in hetero-synaptic neural network, we can get the 2nd equivalent differentialmodel of the hydraulic control system with on-line control operation. This equivalent model provides us with much information, such as stability and the characteristics of the control system.

• Journal of Power Electronics
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• v.3 no.4
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• pp.230-238
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• 2003

Electric vehicles (EV) demands for greater acceleration, performance and vehicle range in pure electric vehicles plus mandated requirements to further reduce emissions in hybrid electric vehicles (HEV) increase the appeal for combined on-board energy storage systems and generators. And the power electronics plays an important role in providing an interface between fuel cells (FC) and loads. This paper deals with a multiple input DC-DC power converter devoted to combine the power flowing of multi-source on energy systems. The multi-source is composed of (i) FC system as a prime power demands, (ii) super capacitor banks as energy storage devices for high and intense power demands, (iii) superconducting magnetic energy storage system (SMES), (iv) multiple input DC-DC power converter and (v) a three phase inverter-fed permanent magnet synchronous motor as a drive. In this system, It is used super capacitor banks and superconducting magnetic energy replaces from the battery system. The modeling and transient performance simulation is effective for reducing transient influence caused by sudden charge of effective load. The main purpose of power electronic converters is to convert the DC power output from the fuel cell and other to a suitable AC voltage, which can be connected to electric loads directly (PMSM). The fuel cell and other output is connected to the DC-DC converter, which regulates the DC link voltage.

• Elastomers and Composites
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• v.55 no.1
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• pp.59-66
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• 2020

Herein, we investigated the thermal conductivity and thermal stability of natural rubber composite systems containing hybrid fillers of boron nitride (BN) and aluminum nitride (AlN). In the hybrid system, the bimodal distribution of polygonal AlN and planar BN particles provided excellent filler-packing efficiency and desired energy path for phonon transfer, resulting in high thermal conductivity of 1.29 W/mK, which could not be achieved by single filler composites. Further, polyethylene glycol (PEG) was compounded with a commonly used naphthenic oil, which substantially increased thermal conductivity to 3.51 W/mK with an excellent thermal stability due to facilitated energy transfer across the filler-filler interface. The resulting PEG-incorporated hybrid composite showed a high thermal degradation temperature (T₂) of 290℃, a low coefficient of thermal expansion of 26.4 ppm/℃, and a low thermal distortion parameter of 7.53 m/K, which is well over the naphthenic oil compound. Finally, using the Fourier's law of conduction, we suggested a modeling methodology to evaluate the cooling performance in thermal management system.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).