• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.81-94
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• 2010

Input variable selection is one of the various techniques for improving the performance of artificial neural network. In this study, mutual information is applied for input variable selection technique instead of correlation coefficient that is widely used. Among 152 variables of RDAPS (Regional Data Assimilation and Prediction System) output results, input variables for artificial neural network are chosen by computing mutual information between rainfall records and RDAPS' variables. At first the rainfall forecast variable of RDAPS result, namely APCP, is included as input variable and the other input variables are selected according to the rank of mutual information and correlation coefficient. The input variables using mutual information are usually those variables about wind velocity such as D300, U925, etc. Several statistical error estimates show that the result from mutual information is generally more accurate than those from the previous research and correlation coefficient. In addition, the artificial neural network using input variables computed by mutual information can effectively reduce the relative errors corresponding to the high rainfall events.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.112-119
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• 2003

Generally, PID controller is not suitable to control multi variable system because it is very difficult to tune the PID gains. However, this paper shows that it is not hard to tune the PID gains if we can find a Jacobian matrix of the system. The Jacobian matrix expresses the ratio of output variations according to input variations. It is possible to adjust the input values in order to reduce the output error using the Jacobian. When the colt function is composed of error related terms, the gradient approach can tune the PID gains to minimize the function. In simulation, a hydrofoil catamaran with two inputs and two outputs is applied as a multi variable system. We can easily get the multi variable PID controller by the proposed teaming method. When the controller is compared with LQR controller, the performance is as good as that of LQR controller with a modeling equation.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.241-247
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• 2014

This paper propose a variable parameter estimations of five-phase squirrel-cage induction motor(IM) for speed control system. In order to high performance control of AC motor using a field oriented control(FOC) and direct torque control(DTC) algorithm, there are required precise motor parameters for slip calculation, flux observer, controller gain, rotor position, speed estimation, and so on. We are suggest a analyzed estimation results of the motor parameters that developing five-phase squirrel-cage IM have a stator of concentrated winding for experimental of variable input power frequency. There are results of stator winding test, no-load test, locked-rotor test, variable actual load test, and estimated parameters of equivalent circuits using manufactured experimental apparatus by IEEE Standard Test Procedure for Polyphase Induction Motors and Generators 112-2004.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.402-406
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• 1990

A new approach of a time-varying switching hyperplane based on the theory of variable structure system (VSS) is proposed for the control of multivariable systems. While the conventional switching surface can net achieve the robust performance against parameter variations and disturbances before the sliding mode occurs, the proposed switching hyperplane, which is obtained from the eigen-structure assignment theory powerfully used in the linear multivariable systems, ensures the sliding mode from the initial state. And new continuous control input which guarantees the sliding mode is proposed. This new control input does not arise chattering problem which arises with the conventional control input of variable structure control systems. Through numerical examples, the expellant performances of the proposed controller are verified.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.764-776
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• 1999

In this paper, a tracking algorithm for a maneuvering single target in the presence of multiple data from multiple sensors is investigated. Allowing individual sensors to function by themselves, the estimates from individual sensors on the same target are fused for the purpose of improving the state estimate. The filtering method adopted in the local sensors is the variable dimensional filter with input estimatio technique, which consists of a constant velocity model and a constant acceleration model. A posteriori probability for the maneuvering hypothesis is newly derived. It is shown that the relation function of the a posteriori probability is a function of only the covariance of the fused estimates. Simulation results are provided.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.211-211
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• 2000

The multiple targets tracking problem has been one of main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimension filter, input estimation filter, interacting multiple model (IMM) filter, federated variable dimension filter with input estimation, probable data association (PDA) filter etc. have been proposed to address the tracking and sensor fusion issues. In this paper, two existing tracking algorithms, i.e. the IMMPDA filter and the variable dimension filter with input estimation (VDIE), are combined for the purpose of improving the tracking performance of maneuvering targets in clutter. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns i.e. Waver, Pop-Up, and High-Diver motions, are defined and are applied to the modified IMMPDA filter considered as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMMPDA filter than the standard IMM filter are demonstrated through computer simulations.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.759-760
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• 2006

In this paper, The author designed on high speed VLD(Variable Length Decoder) using shift buffer. Variable Length Decoder is received N bit data from input block and decode the input signal using Shifting Buffer, Length Decoder and Symbol Decoder blocks. The inner part of shifting buffer in proposed Variable Length Decoder is filled input data and then operating therefore, the proposed structure can improve the decoded speed. And in this paper we applying pipeline structure therefore data is decoded in every clock.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.1999-2001
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• 1997

The main two drawbacks of the Sin91e Stage PFC (SS-PFC) converters employing a DCM Boost PFC cell are relatively high voltage stress on the bulk capacitor and the input current harmonic distortion. The high voltage stress on bulk capacitor makes the SS-PFC converter impractical in a universal input application and the input current harmonic distortion lowers power factor. In this paper a selective variable frequency control that reduces the voltage stress on the bulk capacitor and the input current harmonic distortion is proposed. Computer simulation results of the proposed control method are presented.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.771-780
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• 2007

In recent studies, various types of multi mode electric variable transmissions of hybrid electric vehicles have been proposed. Multi mode electric variable transmission consists of two or more different types of planetary gear hybrid powertrain system(PGHP), which can change its power flow type by means of clutches for improving transmission efficiencies. Generally, the power flows can be classified into three different types such as input split, output split and compound split. In this study, we analyzed power transmission characteristics of the possible six input split systems, and found the suitable system for single or multi mode hybrid powertrain. The input split system used in PRIUS is identified as a best system for single mode, and moreover we identified some suitable systems for dual mode.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2562-2567
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• 2005

This paper suggests a new method discretization of nonlinear system using Taylor series expansion and zero-order hold assumption. This method is applied into the sampled-data representation of a nonlinear system with input time delay. Additionally, the delayed input is time varying and its amplitude is bounded. The maximum time-delayed input is assumed to be two sampling periods. Them mathematical expressions of the discretization method are presented and the ability of the algorithm is tested for some of the examples. And 'hybrid' discretization scheme that result from a combination of the ‘scaling and squaring' technique with the Taylor method are also proposed, especially under condition of very low sampling rates. The computer simulation proves the proposed algorithm discretized the nonlinear system with the variable time-delayed input accurately.