• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.16 no.5
• /
• pp.45-52
• /
• 2002

This paper presents fault detection scheme of Brushless DC(BLDC) motor drive system by estimating BLDC motor resistance using motor input and output data which is transmitted from data acquisition board to host computer over serial communication channel. Since communication time delay has a serious effect on performance, we use periodic and fixed communication protocol. Hence, the delay time is priory known. Simplified BLDC motor model and recursive least square algorithm is used for estimating motor resistance. By experiment result, we confirm the proposed scheme.

• Proceedings of the KIEE Conference
• /
• 2002.07a
• /
• pp.203-205
• /
• 2002

This paper presents the fault location estimation algorithm in transmission line using a recursive least square error method (RLSE). To minimize the computational burden of the digital relay a RLSE approach is used. Computer simulation results of the RLSE algorithm seem promising, indicating that it should be considered for further testing and evaluation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.2
• /
• pp.311-316
• /
• 2007

This paper proposes the algorithm which estimates moment of the inertia and friction coefficient of friction for high performance speed control of electric motor. The proposed algorithm finds the moment of inertia and friction coefficient of friction by observing the speed error signal generated by the speed observer and using Recursive Least-Mean-Square method(RLS). By feedbacking the estimated inertia and estimated coefficient of friction to speed controller and full order speed observer, then the errors of the inertia and coefficient of friction and speed due to the inaccurate initial value are decreased. Inertia and coefficient of friction converge to the actual value within several times of speed changing. Simulation and actual experiment results are given to demonstrate the effectiveness of the proposed parameter estimator.

• Journal of the Korean Society for Precision Engineering
• /
• v.18 no.10
• /
• pp.101-108
• /
• 2001

In this study, the static and dynamic characteristics of endmilling process were modelled and the analytic realization of chatter mechanism was discussed. In this reward, We have discussed on the comparative assessment of recursive time series modeling algorithms that cal represent time machining process and detect the abnormal machining behaviors in precision endmilling operation. In this study, simulation and experimental works were performed to show the malfunctional behaviors. For this purpose, new recursive algorithm(RLSM) was adopted for the oil-line system identification and monitoring of a machining process, we can apply these new algorithms in real process for detection of abnormal chatter. Also, The stability lobe of chatter was analysed by varying parameter of cutting dynamics in regenerative chatter mechanics.

• Journal of Environmental Science International
• /
• v.6 no.5
• /
• pp.541-550
• /
• 1997

A least-square regression analysis is applied for the estimation of velocity streamfunction field based on discretely sampled current meter data. The coefficients of a streamfuunction that is expanded in terms of trigonometric basis function are obtained by enforcing the horizontal non-divergence of two-dimensional flow field. This method avoids Interpolation and gives a root-mean-square (rms) residual of fit which Includes the divergent part and noisiness of oceanic data. The Implementation of the method Is done by employing a boundary-fitted, curvilinear orthogonal coordinate which facilitates the specification of boundary conditions. An application is successfully made to the Texas-Louisiana shelf using the 32 months current meter data (31 moorings) observed as a part of the Texas-Louisiana Shelf and Transport Processes Study (LATEX). The rms residual of the fitting is relatively small for the shelf, which indicates the field Is Ivell represented by the streamnfunction.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.1
• /
• pp.99-106
• /
• 2015

In this study, we propose Radial basis function Neural Network(RBFNN) using Recursive Weighted Least Square Estimation(RWLSE) to effectively deal with big data class meteorological radar data. In the condition part of the RBFNN, Fuzzy C-Means(FCM) clustering is used to obtain fitness values taking into account characteristics of input data, and connection weights are defined as linear polynomial function in the conclusion part. The coefficients of the polynomial function are estimated by using RWLSE in order to cope with big data. As recursive learning technique, RWLSE which is based on WLSE is carried out to efficiently process big data. This study is experimented with both widely used some Machine Learning (ML) dataset and big data obtained from meteorological radar to evaluate the performance of the proposed classifier. The meteorological radar data as big data consists of precipitation echo and non-precipitation echo, and the proposed classifier is used to efficiently classify these echoes.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.44 no.6
• /
• pp.1-10
• /
• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• Journal of Korean Society of Transportation
• /
• v.19 no.6
• /
• pp.89-102
• /
• 2001

Using a multiproduct translog cost function model, this paper examines the existence or absence of scale and scope economies in Seoul's urban bus industry. The Paper then conceptualizes that the bus firm produces three outputs (city, seat and local bus-kilometers) using low input factors(labor, capital, fuel and maintenance). Using 1996 annual observations for 81 Seoul's bus firms, the equation system consisting of a cost function and three input share equations is estimated with the nonlinear iterative Zellner method. The findings show that the cost function corresponding to a non-homothetic production technology with separability between local bus outputs and inputs adequately represents the structure of cost for Seoul's bus firms, and that the demand lot all input factors is quite inelastic with respect to their own price. On the other hand, nearly all firms experience mild overall economies or scale, but rather marked product-specific economies of scale with respect to all the three outputs. In addition, there appear to be substantial economies or scope associated with the joint production of city and seat bus services, while considerable diseconomies of scope associated with that of city and local bus services. These results indicate that the merger of smaller firms into larger firms with a fleet of approximately 200 buses would result in more cost-efficient bus services.

• Nuclear Engineering and Technology
• /
• v.27 no.3
• /
• pp.336-343
• /
• 1995

The Self Tuning Regulator(STR) method which is an approach of adaptive control theory, is ap-plied to design the fully automatic power controller of the nonlinear reactor model. The adaptive control represent a proper approach to design the suboptimal controller for nonlinear, time-varying stochastic systems. The control system is based on a third­order linear model with unknown, time-varying parameters. The updating of the parameter estimates is achieved by the recursive extended least square method with a variable forgetting factor. Based on the estimated parameters, the output (average coolant temperature) is predicted one-step ahead. And then, a weighted one-step ahead controller is designed so that the difference between the output and the desired output is minimized and the variation of the control rod position is small. Also, an integral action is added in order to remove the steady­state error. A nonlinear M plant model was used to simulate the proposed controller of reactor power which covers a wide operating range. From the simulation result, the performances of this controller for ramp input (increase or decrease) are proved to be successful. However, for step input this controller leaves something to be desired.

• International Area Studies Review
• /
• v.15 no.3
• /
• pp.239-261
• /
• 2011

The cyclicality of productivity has been one of the essential issues in macroeconomics. Since Solow(1957) developed the dominant approach to the measurement of productivity growth, Solow's approach, which assumes the perfect competition, the constant returns to scale, and the full use of input factor has been modified particularly in Hall's(1990) and Basu's(1996) works. Their researches take account of market power, returns to scale, and variable factor utilization. This paper establishes the empirical model based on Hall's(1990) and Basu's(1996) models, estimates 4 types of Solow's reidual in manufacturing and 2 service industries over the period 1975:1-2010:4, and analyzes the cyclicality of measured productivity. The result proved the measured productivity to be procyclical in manufacturing industries and electricity and water industry, and in contrast to the Basu's, the variable factor utilization transformed the countercyclicality of measured productivity into its procyclicality in the Korean economy.