• Journal of Information Technology and Architecture
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• v.11 no.4
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• pp.441-448
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• 2014

The application of spatial information has drawn significant attention from a wide range of industries. Railway spatial information facilitates the cooperation among related parties and improves the efficiency of asset management and operations. This study proposes the structure of Railway Object IDentifier(ROID) on railway spatial information. Current facility management and train operation are based on relative positioning system. Despite many advantages, relative positioning system causes serious problems such as the entire reconfiguration of positioning in the case of line change. Another major concern is the interface compatibility between individual facilities with different relative positioning. ROID based on absolute positioning addresses these issues, allowing the information exchange and convergence between independent parties. This study proposes ROID based on OID standard with object IDentifier and service object-oriented reference system. Our ROID employs the absolute positioning and the unique identifier, maintaining the compatibility with existing management system.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.13-18
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• 1996

A real-time identifier for the nonstationary time-varying signals and systems was implemented using a low cost DSP (digital signal processing) chip. The identifier is comprised of I/O units, a central processing unit, a control unit and its supporting software. In order t estimate the system accurately and to reduce quantization error during arithmetic operation, the firmware was programmed with 64-bit extended precision arithmetic. The performance of the identifier was verified by comparing with the simulation results. The implemented real-time identifier has negligible quantization errors and its real-time processing capability crresponds to 0.6kHz for the nonstationary AR (autoregressive) model with n=4 and m=1.

• Proceedings of the KIEE Conference
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• 1996.07b
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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.

• IE interfaces
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• v.20 no.2
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• pp.227-234
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• 2007

The national product identifier(NPI) currently used in the national product asset management system does not accommodate ISO or EPC standards due to the limitation of tag memory. For this reason, we propose a new NPI which accommodates not only ISO item identification standards but also the memory capacity of ISO tags. First of all, memory structures of ISO/IEC 18000-6C and EPC tags are analyzed from the view point of product identifier structure. Second, ISO/IEC 15459 and EPC identification standards as item identifier structures for the product asset management are analyzed. Third, based on these analyses, the NPI used for the current RFID-based product asset management system is analyzed and its problems are presented. Finally, a new NPI structure is proposed suitable for ISO/IEC 18000-6C and ISO/IEC 15459.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.543-552
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• 1994

This paper presents a decentralized quadratic regulation architecture with feedforward neural networks for the control problem of complex systems. In this method, the decentralized technique was used to treat several simple subsystems instead of a full complex system in order to reduce training time of neural networks, and the neural networks' nonlinear mapping ability is exploited to handle the nonlinear interaction variables between subsystems. The decentralized regulating architecture is composed of local neuro-controllers, local neuro-identifiers and an overall interaction neuro-identifier. With the interaction neuro-identifier that catches interaction characteristics, a local neuro-identifier is trained to simulate a subsystem dynamics. A local neuro-controller is trained to learn how to control the subsystem by using generalized Backprogation Through Time(BTT) algorithm. The proposed neural network based decentralized regulating scheme is applied in the power System Stabilization(PSS) control problem for an imterconnected power system, and compared with that by a conventional centralized LQ regulator for the power system.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.15-29
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• 2004

With the rapid growth of information technology and the internet. the physical contents are transformed into digital contents at a fast rate. With the change. accessing the digital contents, toe service methods and the identifier used for the digital contents are not systematic and limited for use. The DOI identifier system used for the URN is also limited to academic journals or magazines and are not adequately applicable for non-academic journal or digital contents. Therefore. we have developed a unique identifier based on the analysis made on the system adopted by foreign digital contents service institutes. two types of academic journals 3 types of non-academic journals owned by KISTI that can be adopted by non-academic journals. The identifier is to be used to design and implement a digital contents service system.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.61-65
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• 1997

This paper proposes an intelligent controller for brushless DC motor and load with unknown nonlinear dynamics. The proposed intelligent control system consists of a plant identifier and PID controller with varying gains. The identifier is constructed using an Auto Regressive Moving Average (ARMA) model. In order to tune the parameters of the identifier and the gains of the PID controller efficiently, e also propose a modified Evolution Strategy. Experimental results show that the proposed intelligent controller for brushless DC motor has good control performance under unknown disturbance.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.776-778
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• 1999

In this paper, identifier for thermal storage system using multi-layer feedforward neural network (MFNN) is designed. It is very difficult to control thermal storage system, since thermal storage system is nonlinear and its time constant is very large. Thus, in the MFNN, delta-bar-delta algorithm for high running speed and 2-bit status input are used. Also hardware using microprocessor for identifier is developed. The experimental results indicate that the proposed method can predict temperature more accurately.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.927-930
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• 1992

VSS identification approach is based on following concept, i.e. while in sliding motion, the switching of control inputs refects system uncertainites. Therefore, if there exist some operations that make the information form the switiching control inputs be achievable, then the unknown parameters can be actually identification mechanisms which can fully make use of the available information. Two different types of VSS identifiers are taken into consideration. The first type uses adjustable model whose structure is similar to that of identified systems. From the viewpoint of contro, this type of VSS identifiers may be regraded as direct identifier vecause the identified system is handled as an open loop. On the other hand, if the identified system is controlable in the sense of VSS(sliding mode can be generated through chosing control inputs), the second type of VSS identifier, the indirect VSS identifier, can be constructed according to the linerized system strucutre while staying in sliding mode. Therefroe it can be applied to some nonlinear systems which are not linear in parametric space by general identification algorithms, whereas linear in parametric space when sliding mode is existed.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.194-201
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• 2005

In this paper, we propose an adaptive mechanism based on humoral immune algorithm and neural network identifier technique. It is also applied for an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To slove this problem, we use the neural network identifier technique for modeling the plant humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. Finally, the experimental results for control of steering and speed of AGV system illustrate the validity of the proposed control scheme. Also, these results for the proposed method show that it has better performance than other conventional controller design method such as PID controller.