• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.165-172
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• 1998

The electromechanical energy conversion conditioning and processing implementation in USM direct motion control system is generally divided into two power stages: the two-phase high-frequency ac power inversion stage for driving piezoelectric ceramic PZT transducer array off the USM stator and the mechanical thrust power conversion stage based on the frictional force between the piezo electric stator array and the rotary slider of the USM. However, the dynamic and steady-state mathematical modeling of the USM is extremely default from a theoretical point of view because it contains many complicated an nonlinear characteristics dependant on operation temperature. In +2$0^{\circ}C$~3$0^{\circ}C$, the operating characteristics of the USM has represented normal condition. But the other temperature, it has abnormal condition so that driving frequency, current and motor speed will be down. The recent USM has controller without temperature compensation. This study represents the fuzzy controller for speed compensation according to operating temperature by driving frequency.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.10
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• pp.851-857
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• 2014

This paper addresses the design of the auto race-track and figure-8 flight mode which can be applied to expand the loitering flight mode and increase the safety of UAV. To implement these flight modes, necessary waypoints and entry points can be calculated automatically from several information of the ground control system. The flight logic is proposed to pass the desired waypoints as well as entry points and transfer to the desired flight path by combining the light-of-sight and loitering guidance controller. The proposed algorithm and logic is verified using the 6-DOF UAV model and nonlinear simulation under the several flight conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.402-410
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• 2004

In this paper, an optimal design method of clonal selection based Fuzzy-Neural Networks (FNN) model for complex and nonlinear systems is presented. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. Also Advanced Clonal Selection (ACS) is proposed to find the parameters such as parameters of membership functions, learning rates and momentum coefficients. The proposed method is based on an Immune Algorithm (IA) using biological Immune System and The performance is improved by control of differentiation rate. Through that procedure, the antibodies are producted variously and the parameter of FNN are optimized by selecting method of antibody with the best affinity against antigens such as object function and limitation condition. To evaluate the performance of the proposed method, we use the time series data for gas furnace and traffic route choice process.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.28-35
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• 2012

This paper presents the method for $H_{\infty}$ fuzzy controller design of discrete-time fuzzy Markovian jump systems with state and input time delays. The Takagi and Sugeno fuzzy model is employed to represent a delayed nonlinear system that possesses Markovian jump parameters. A stochastic mode dependent Lyapunov function is employed to analyze the stability and $H_{\infty}$ disturbance attenuation performance of the fuzzy Markovian jump systems with state and input time delays. A sufficient condition for the existence of fuzzy $H_{\infty}$ controller is given in terms of matrix inequalities. Also numerical example is presented to illustrate the efficiency of the proposed design method.

• Earthquakes and Structures
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• v.15 no.2
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• pp.133-144
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• 2018

To study the effectiveness of sliding isolation in a CRLSS (concrete rectangular liquid-storage structure) and develop a reasonable limiting-device method, dynamic responses of non-isolation, sliding isolation with spring limiting-devices and sliding isolation with steel bar limiting-devices are comparatively studied by shaking table test. The seismic response reduction advantage of sliding isolation for concrete liquid-storage structures is discussed, and the effect of the limiting-device type on system dynamic responses is analyzed. The results show that the dynamic responses of sliding isolation CRLSS with steel bar-limiting devices are significantly smaller than that of sliding isolation CRLSS with spring-limiting devices. The structure acceleration and liquid sloshing wave height are greatly influenced by spring-limiting devices. The acceleration of the structure in this case is close to or greater than that of a non-isolated structure. Liquid sloshing shows stronger nonlinear characteristics. On the other hand, sliding isolation with steel bar-limiting devices has a good control effect on the structural dynamic response and the liquid sloshing height simultaneously. Thus, a limiting device is an important factor affecting the seismic response reduction effect of sliding isolation. To take full advantage of sliding isolation in a concrete liquid-storage structure, a reasonable design of the limiting device is particularly important.

• Journal of the Korea Concrete Institute
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• v.21 no.5
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• pp.549-556
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• 2009

This research analyzed the structural efficiency and application by improving the 100 mm width vertical joint to 150 mm and developing three connection methods to reduce the difficulty in assembling and handling PC walls. Moreover, nonlinear finite analysis was used for analyzing. From the analysis results, when double width connection was applied, the PC wall showed larger load capacity and ductility due to the steel bar sharing loads efficiently. Moreover, as the dimension of loops and the number of bars increased, the maximum load capacity increased as well. Also, among the double width connections, the largest capacity showed in the order of welding, ring and C type loop. However, in case of welding type loop connection, the ring type loop is more stable due to changes in different site conditions. Therefore, thorough quality control of welding is necessary.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.6
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• pp.40-47
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• 2007

High speed electric trains have nonlinear loads including converters and inverters for the control synchronous motors. Harmonic field measurements have shown that the harmonic contents of a waveform varies with time. Direct application of the harmonic assessment to the snapshot measurements would result in ambiguous conclusions depending on which instant is sampled. A cumulative probablistic approach is the most commonly used method to solve time varying harmonics. Harmonic simulations are performed to evaluate the harmonic voltage and current distortions throughout the system. This paper provides an in depth analysis on harmonics field measurement of the high speed electric train loads, harmonics assessment by the international harmonic standards IEC 61000-3-6 and IEEE Std. 519-l992, and harmonics simulation using EDSA program for the case study.

• Journal of Korean Society on Water Environment
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• v.22 no.3
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• pp.546-556
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• 2006

The purpose of this study is to improve the polluted stream water quality by pilot-scale five different constructed wetlands (CWs). Cell 1 to 3 are newly designed 2SFCW (Surface-subsurface flow CW) with 1 to 3 flow shifters (FS) in the middle of the wetland system. Cell 4 and 5 are control CW (CCW), but Cell 5 is the same type as Cell 3. The FS, which converts the route of surface and subsurface flow between two wetlands connected in series, was able to enhance the treatability of TN via nitrification and denitrification and of SS due to filtration and sedimentation. The void fraction and dispersion number of Cell 1, 2 and 3 obtained from the RTD analysis were found to be 0.73 and 0.17, respectively. COD and TP removal efficiencies of Cell 1 to 3 were similar to that of Cell 4 and 5. SS removal efficiencies of Cell 1 to 3 and 5 with FS were 5-10% higher than that of Cell 4 without FS. TN removal efficiencies of Cell 1 to 3 were 3-14% higher than that of Cell 4 and 5. The average $R^2$ values of COD, SS, TN and TP obtained from nonlinear regression analysis were similar to the results of other researchers.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3275-3285
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• 2021

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.249-255
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• 2011

The free-stereo mosaics image without GPS/INS and ground control data can be generated by using relative orientation parameters on the 3D model coordinate system. Its origin is located in one reference frame image. A 3D coordinate calculated by conjugate points on the free-stereo mosaic images is represented on the 3D model coordinate system. For determining 3D coordinate on the 3D absolute coordinate system utilizing conjugate points on the free-stereo mosaic images, transformation methodology is required for transforming 3D model coordinate into 3D absolute coordinate. Generally, the 3D similarity transformation is used for transforming each other 3D coordinates. Error of 3D model coordinates used in the free-stereo mosaic images is non-linearly increased according to distance from 3D model coordinate and origin point. For this reason, 3D model coordinates used in the free-stereo mosaic images are difficult to transform into 3D absolute coordinates by using linear transformation. Therefore, methodology for transforming nonlinear 3D model coordinate into 3D absolute coordinate is needed. Also methodology for resampling the free-stereo mosaic image to the geo-stereo mosaic image is needed for overlapping digital map on absolute coordinate and stereo mosaic images. In this paper, we propose a 3D non-linear transformation for converting 3D model coordinate in the free-stereo mosaic image to 3D absolute coordinate, and a 2D non-linear transformation based on 3D non-linear transformation converting the free-stereo mosaic image to the geo-stereo mosaic image.