• Proceedings of the KIPE Conference
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• 1997.07a
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• pp.89-96
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• 1997

A robust speed control scheme for a brushless DC(BLDC) motor using an adaptive input-output linearization technique is presented. By using this technique, the nonlinear motor model can be linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative experiments.

• Journal of Electrical Engineering and information Science
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• v.2 no.3
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• pp.113-122
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• 1997

An adaptive input-output linearization technique for a robust speed control of a brushless C(BLDC) motor is presented. By using this technique, the nonlinear moro model can be effectively linearized in Brunovski canonical form, an the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions caused by the incomplete linearization. for the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov's hyperstability theory nd positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative simualtions and experiments.

• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.94-102
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• 2012

Recently, the global financial crisis and the increasing number of unsold houses in Korea are construction companies to assess their efficiency. The most important factor in analyzing the efficiency of a company is the input-output variable. However, systematic stud the core input-output variables, which have a great influence on the efficiency analysis. Thus, to the core input-output variables for efficiency analysis of construction companies, this study propose a model that includes all combinations of input-output variables and to find the core input-output variables using the Data Envelopment Analysis(DEA) model and Principal Component Analysis(PCA). Existing research and theories were studied variables and 21 models were established to measure efficiency. were obtained that the core input and output variable in 2006 the number of employees and sales. For 2008, the core input variable was capital stock and the core output variable was quarterly net profit. For 2010, the core input variable was fixed asset and the core output variable was sales. Through obtaining the variables that greatly affect the efficiency of construction companies, it is considered that individual construction companies will be able to prepare a priority strategy to enhance efficiency.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.183-193
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• 2007

This paper shows that a response function for the center of fuzzy output nay not be the same as that for the spread in a fuzzy linear regression model and then suggests a separate fuzzy regression model makes a distinction between response functions of the center and the spread of fuzzy output. Also we use a least squares method to estimate the separate fuzzy regression model and compare an accuracy of proposed model with another fuzzy regression model developed by Diamond (1988) and Kao and Chyu (2003).

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1222-1227
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• 1990

The problem of identification of continuous systems is considered when both the discrete input and output measurements are contaminated by white noises. Using a predesigned digital low-pass filter, a discrete-time estimation model is constructed easily without direct approximations of system signal derivatives from sampled data. If the pass-band of the filter is designed so that it includes the main frequencies of both the system input and output signals in some range, the noise effects are sufficiently reduced, accurate estimates can be obtained by least squares(LS) algorithm in the presence of low measurement noises. Two classes of filters(infinite impulse response(IIR) filter and finite impulse response(FIR) filter) are employed. The former requires less computational burden and memory than the latter while the latter is suitable for the bias compensated least squares(BCLS) method, which compensates the bias of the LS estimate by the estimates of the input-output noise variances and thus yields unbiased estimates in the presence of high noises.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.273-275
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• 2006

In this paper, we introduce a new design of fuzzy neural networks using input-output data information of target system. The proposed fuzzy neural networks is constructed by input-output data information and used the center of data distance by HCM clustering to obtain the characteristics of data. A membership function is defined by HCM clustering and is applied input-output dat included each rule to conclusion polynomial functions. We use triangular membership functions and simplified fuzzy inference, linear fuzzy inference, and modified quadratic fuzzy inference in conclusion. In the networks learning, back propagation algorithm of network is used to update the parameters of the network. The proposed model is evaluated with benchmark data.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.371-378
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• 2011

This paper examines the estimate the economic impact of 2008 Andong Maskdance Festival, using an Input-Output(I-O) model. For the research, the Regional Input-Output analysis was used, which makes it easy to grasp the economic impact of the tourism industry and other industries in Andong. Based on the regional I-O transactions tables which were developed by Bank of Korea(2009), the industry multipliers were derived with respect to output, income, and value-added. The results show that in 2008 Andong Maskdance Festival receipts generated output impact of 30,961 million won and 15,800 million won of income impact, 14,310 million won of value-added impact, respectively. I think the result of this study can be used as an objective indicator to help to establish and implement regional festival policies for the local government.

• STI Policy Review
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• v.1 no.2
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• pp.51-68
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• 2010

This paper compares OECD nations by developing a comprehensive evaluation index that examines the efforts and achievements of countries toward Low-Carbon Green Growth. The input-process-output of a Low-Carbon Society system is in dynamic competition with that of a High-Carbon Society system. The model used in this study of the comprehensive evaluation index for Low-Carbon Green Growth was comprised of Large indices such as Input, Process, and Output. The Input and Output consisted of 'Social-economic' and 'Physical-ecological' Middle indices while the Process was made up of 'Stimulation mechanisms' and 'Participation of stakeholders and Knowledge flow' Middle indices. In order to calculate the comprehensive evaluation index, our model gave a weight to each indicator/index and applied a weighted arithmetic mean. Korea ranked $15^{th}$ out of 30 OECD nations in the comprehensive evaluation that analyzed Input ($14^{th}$), Process ($18^{th}$), and Output ($17^{th}$). The top five nations were Switzerland, Sweden, Denmark, Germany, and France; while Japan was $8^{th}$ and the USA $26^{th}$.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.5
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• pp.398-412
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• 2023

The Korean government is actively promoting the hydrogen industry as a key driver of economic growth. This commitment is evident in the 2019 hydrogen economy activation roadmap and the 2021 basic plan for hydrogen economy implementation. This study quantitatively analyzes the economic impact of the hydrogen economy using input-output analysis based on the Bank of Korea's 2019 input-output table, projecting its size by 2050. Four parts dealt with production-inducing, value-added creation, employment-inducing, and wage-inducing based on a demand-driven model. The results reveal that transportation had the most remarkable economic effect throughout the hydrogen economy, and production was the least. The hydrogen economy is projected to reach 71.2 trillion won by 2050.

• Korean Management Science Review
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• v.15 no.2
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• pp.125-142
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• 1998

The aggregation on linear large-scale dynamic systems is examined in this paper and a "two-step" approach is proposed. In this procedure, the aggregated system consists of two subsystems. The first subsystem represents aggregation through the retainment of dominant eigenvalues of the original system, leading to a first approximation of the desired output of the original system. The purpose of augmenting it with a second subsystem is to provide an estimation of the error on the first approximation, thus permitting a second correction to the output approximation and resulting in an output approximation of greater accuracy. Optimization techniques are discussed for the determination of unknown parameters in the aggregated system. These techniques use minimization principles of certain suitable performance indices and are developed for both single input-single output and multiple input-multiple output system. Numerical examples illustrating these procedures are given and the results are compared with those obtained using existing methods. Finally, a pharmacokinetics problem is studied from the aggregation point of view.