• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1001-1002
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• 2007

This study investigates the dynamic characteristics of Synchronous Reluctance Motor (SynRM), with segmental rotor structure, using finite element method in which the moving mesh technique is considered. The focus of this paper is the efficiency of on-line parameter identification system for position sensorless control of a SynRM under saturation and iron loss. Comparisons are given with angle of the observer and those of proposed FEM & Preisach model of synchronous reluctance motor, respectively. The position sensorless control using identified motor parameters is realized, and the effective of the on-line parameter identification system is verified by experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.118-124
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• 2004

In this paper, we present a indirect adaptive control method using a wavelet neural network (WNN) for the control of chaotic nonlinear systems without precise mathematical models. The proposed indirect adaptive control method includes the off-line identification and on-line control procedure for chaotic nonlinear systems. In the off-line identification procedure, the WNN based identification model identifies the chaotic nonlinear system by using the serial-parallel identification structure and is trained by the gradient-descent method. And, in the on-line control procedure, a WNN controller is designed by using the off-line identification model and is trained by the error back-propagation algorithm. Finally, the effectiveness and feasibility of the proposed control method is demonstrated with applications to the chaotic nonlinear systems.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.250-258
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• 2003

In this paper, an explanation regarding on-line identification of a fuzzy system is presented. The fuzzy system to be identified is assumed to be in the type of singleton consequent parts and be represented by a linear combination of fuzzy basis functions. For on-line identification, squared-cosine membership function is introduced to reduce the number of parameters to be identified and make the system consistent and differentiable. Then the parameters of the fuzzy system are identified on-line by the gradient search method and Extended Kalman Filter. Finally, a computer simulation is peformed to illustrate the validity of the suggested algorithms.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.729-736
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• 2013

Power grids are large complicated networks in use around. An absolute phase value for a particular unknown-phase line at a local site should be identified for the operation and management of a 3-phase distribution network. The phase shift for a specific point in the line, as compared with a phase reference point at a substation, must be within a range of ${\pm}60^{\circ}$ for correct identification. However, the phase shift at a particular point can fluctuate depending on the line constants, transformer wiring method, line length, and line amperage, etc. Conducted in this study is a theoretical formulation for the determination of phase at a specific point in the line, Simulink modeling, and analysis for a distribution network. In particular, through evaluating the effects of unbalanced current loads, the limitations of the present phase identification methods are described.

• Smart Structures and Systems
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• v.24 no.5
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• pp.617-630
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• 2019

Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2103-2108
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• 2007

This study investigates the dynamic characteristics of Synchronous Reluctance Motor (SynRM), with segmental rotor structure, using finite element method in which the moving mesh technique is considered. The focus of this paper is the efficiency of on-line parameter identification system for position sensorless control of a SynRM considering saturation and iron loss. Comparisons are given with angle of the observer and those of proposed FEM & Preisach model of synchronous reluctance motor, respectively. The position sensorless control using identified motor parameters is realized, and the efficiency of the on-line parameter identification system is verified by experimental results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.204-210
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• 1998

This paper discusses an on-line fuzzy dynamic model(FDM) identification of nonlinear processes for the design of fuzzy model based fault detection and isolation(FDI). The dynamic behavior of a nonlinear process is represented by a fuzzy aggregation of a set of local linear models. The identification is divided into two procedures. The first is the off-line identification of membership function. The second is the on-line identification of the local linear models. Then, we propose a residual generation scheme based on the parameters of local linear models and show that the scheme can be used for the design of FDI

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1754-1763
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• 2017

This paper analyses the characteristics of incomplete-journey double-circuit transmission lines on the same tower formed by single-circuit lines and double-circuit lines, and then presents a fault location algorithm based on identification of fault branch. With the relationship between the three-phase system and the double-circuit line system, a phase-mode transformation matrix for double-circuit lines can be derived. Based on the derived matrix, the double-circuit lines with faults can be decoupled, and then the fault location for an incomplete-journey double-circuit line is achieved by using modal components in the mode domain. The algorithm is divided into two steps. Firstly, the fault branch is identified by comparing the relationships of voltage amplitudes at the bonding point. Then the fault location, on the basis of the identification result, is calculated by using a two-terminal method, and only the fault distance of the actual fault branch can be obtained. There is no limit on synchronization of each terminal sampling data. The results of ATP-EMTP simulation show that the proposed algorithm can be applied within the entire line and can accurately locate faults in different fault types, fault resistances, and fault distances.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.48-54
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• 1994

A recursive on-line algorithm with orthogonal ARMA identification is proposed for linear systems with unkonwn time delay, order, and parameters. The algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extendedto recursive form by using two dimensional autocorrelations and crosscorrelations of input and output with constant data length. The proposed algorith can cope with slowly time-varying or order-varying delayed system. Various simulations reveal the performance of the algorithm.

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.161-168
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• 2016

This paper presents a methodology through which the time series of the dynamic response of mooring line tension can be predicted without relying on a time-consuming nonlinear time-domain analysis. The mooring line tension for the target short-term sea states was predicted using a Hammerstein-Wiener model, a popular system identification scheme, based upon the pre-calculated motion-tension time history data for some selected short-term sea states that do not overlap with the targeted ones. The obtained mooring line tension was further processed, and a fatigue damage comparison was made between the predicted and calculated values. The results showed that the predicted time series of the mooring line tension matched the calculated one fairly well. Thus, it is expected that the methodology may be employed to enhance the efficiency of mooring line tension analysis.