• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2538-2541
• /
• 2005

This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

• Journal of Electrical Engineering and Technology
• /
• v.6 no.1
• /
• pp.1-7
• /
• 2011

This paper proposes an enhanced noise robust algorithm for fault location on double-circuit transmission line for the case of single line-to-ground (SLG) fault, which uses distributed parameter line model that also considers the mutual coupling effect. The proposed algorithm requires the voltages and currents from single-terminal data only and does not require adjacent circuit current data. The fault distance can be simply determined by solving a second-order polynomial equation, which is achieved directly through the analysis of the circuit. The algorithm, which employs the faulted phase network and zero-sequence network with source impedance involved, effectively eliminates the effect of load flow and fault resistance on the accuracy of fault location. The proposed algorithm is tested using MATLAB/Simulink under different fault locations and shows high accuracy. The uncertainty of source impedance and the measurement errors are also included in the simulation and shows that the algorithm has high robustness.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2000.11a
• /
• pp.163-166
• /
• 2000

This paper presents an image processing algorithm which gives an sketch effect on the real image taken by CCD camera. The essence of the technique is the expression of shading by the line touch. Several line patterns are developed to emulate pencil drawings, fusains, Indian ink paintings. This algorithm is expected to be used for computer portraits, character development, and souvenirs.

• Proceedings of the KIEE Conference
• /
• summer
• /
• pp.619-621
• /
• 2004

This paper presents the rapid and accurate algorithm for fault discrimination in transmission lines. When faults occur in transmission lines, fault discrimination is very important. If high impedance faults occur in transmission lines, it cannot be detected by overcurrent relays. The method using current and voltage cannot discriminate high impedance fault. Because of this reason this paper uses voltage and zero sequence current, and the proposed algorithm uses fuzzy logic method. This algorithm uses voltage and zero sequence current per period in case of faults. Single line ground fault and three-phase fault can be detective using voltage. Two-line ground fault and line to line fault and high impedance can be detected using zero sequence current. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.

• The Transactions of the Korean Institute of Electrical Engineers C
• /
• v.54 no.5
• /
• pp.206-212
• /
• 2005

In this paper, criterion and algorithm for on-line dissolved gas of a Power transformer are studied. For the initial diagnosis of a power transformer, the on-line dissolved gas analysis is one of the most important and acceptable item to preventively diagnose a power transformer. But the criterion and algorithm of this item are not established yet in korea. In this paper, criterion and alarm level of the on-line dissolved gas analysis are based on the analysis of on-line data of operating transformers, Korea industrial standard and operation manual for a power transformer as well as accumulated data of the preventive diagnosis systems which have been operated at nine substations of Korea Electric Power Co.(KEPCO) since 1997, Therefore, the criterion and alarm level proposed in this paper are to be well suitable and are adaptable for the domestic operational environments and conditions of the power transformer. Considering that the conventional diagnosis system is capable only of accumulating and monitoring data of the power transformer operation, the criteria and the algorithms make it possible to accomplish an ultimate goal of the preventive diagnosis system. It is expected, therefore, that they will have a beneficial effect on broad applications of the preventive diagnosis system and the achievement of manless substation system in the future.

• Proceedings of the IEEK Conference
• /
• 2003.07c
• /
• pp.2581-2584
• /
• 2003

In this paper, we propose a self-localization algorithm using vertical line segments. Indoor environment is consist of horizontal and vertical line features such as doors, furniture, and so on. From the input image, vertical line edges are detected by an edge operator, Then, line segments are obtained by projecting edge image vertically and detecting local maximum from the projected histogram. From the relation of horizontal position of line segments and the location of the robot, nonlinear equations are come out Localization is done by solving the equations by using Newton's method. Experimental results show that the proposed algorithm using one camera is simple and applicable to indoor environment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.1
• /
• pp.21-25
• /
• 1996

In this paper we suggest a general purpose RNN training algorithm which is derived on the optimal control concepts and variational methods. First, learning is regared as an optimal control problem, then using the variational methods we obtain optimal weights which are given by a two-point boundary-value problem. Finally, the modified gradient descent algorithm is applied to RNN for on-line training. This algorithm is intended to be used on learning complex dynamic mappings between time varing I/O data. It is useful for nonlinear control, identification, and signal processing application of RNN because its storage requirement is not high and on-line learning is possible. Simulation results for a nonlinear plant identification are illustrated.

• Proceedings of the KIEE Conference
• /
• 1998.07c
• /
• pp.1111-1113
• /
• 1998

A robust economic dispatch algorithm involving transmission losses is proposed and investigated for a possibility of on-line applications. In this paper, the penalty factors are calculated directly from transposed Jacobian of load flow analysis with advantages of superiority to B-coefficients method based on its computation time and suitability for real time application since the approach is based on a current system condition. The proposed algorithm is systematically handling the generation capacity constraints with transmission losses. Implementation of the algorithm for IEEE systems and EPRI Scenario systems shows that computation time is enough to apply on-line economic dispatch to large power system and production cost is saved compared with the crude classical economic dispatch algorithm without considering transmission losses.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.137-140
• /
• 1996

Finding line segments in an intensity image has been one of the most fundamental issues in computer vision. In complex scenes, it is hard to detect the locations of point features. Line features are more robust in providing greater positional accuracy. In this paper we present a robust "line features extraction" algorithm which extracts line feature in a single pass without using any assumptions and constraints. Our algorithm consists of five steps: (1) edge scanning, (2) edge normalization, (3) line-blob extraction, (4) line-feature computation, and (5) line linking. By using edge scanning, the computational complexity due to too many edge pixels is drastically reduced. Edge normalization improves the local quantization error induced from the gradient space partitioning and minimizes perturbations on edge orientation. We also analyze the effects of edge processing, and the least squares-based method and the principal axis-based method on the computation of line orientation. We show its efficiency with some real images.al images.

• Korean Journal of Remote Sensing
• /
• v.28 no.1
• /
• pp.55-67
• /
• 2012

Real-time image georeferencing is required to generate spatial information rapidly from the image sequences acquired by multi-sensor systems. To complement the performance of position/attitude sensors and process in real-time, we should employ on-line aerial triangulation based on a sequential estimation algorithm. In this study, we thus attempt to derive an efficient on-line aerial triangulation algorithm for real-time georeferencing of image sequences. We implemented on-line aerial triangulation using the existing Given transformation update algorithm, and a new inverse normal matrix update algorithm based on observation classification, respectively. To compare the performance of two algorithms in terms of the accuracy and processing time, we applied these algorithms to simulated airborne multi-sensory data. The experimental results indicate that the inverse normal matrix update algorithm shows 40 % higher accuracy in the estimated ground point coordinates and eight times faster processing speed comparing to the Given transformation update algorithm. Therefore, the inverse normal matrix update algorithm is more appropriate for the real-time image georeferencing.