• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.9
• /
• pp.173-181
• /
• 2014

This paper addresses the problem of model matching control for a class of systems modeled as input/output asynchronous sequential machines. Based on the feedback control scheme, we design a corrective controller that compensates the behavior of the closed-loop system so as to match a reference model. Whereas the former studies use state observers and the output burst for designing a controller, the present research needs neither the observer nor the output burst in controller design. We define the 'output equivalent machine' of the considered machine to describe the existence condition and the construction algorithm for the proposed controller. A case study is provided to show the operation of the proposed corrective controller.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.6C
• /
• pp.490-496
• /
• 2005

In this paper, we propose a self-constructed clustering algorithm based on inference information of the fuzzy model. This method makes it possible to automatically detect and optimize the number of cluster and parameters by using input-output data. The propose method improves the performance of clustering by extended supervised learning technique. This technique uses the output information as well as input characteristics. For effect the similarity measure in clustering, we use the TSK fuzzy model to sent the information of output. In the conceptually, we design a learning method that use to feedback the information of output to the clustering since proposed algorithm perform to separate each classes in input data space. We show effectiveness of proposed method using simulation than previous ones

• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.1
• /
• pp.50-58
• /
• 2017

For nonlinear control system design, there are many studies based on TSK fuzzy model. However, TSK fuzzy modelling needs nonlinear dynamic equations of the object system or a data set fully distributed in input-output space. This paper proposes an modelling technique using only step input response data. The technique uses also the genetic algorithm. The object systems in this paper are nonlinear to control input variable or output variable. In the case of nonlinear to control input, response data obtained with several step input values are used. In the case of nonlinear to output, step input response data and zero input response data are used. This paper also presents a fuzzy controller design technique from TSK fuzzy model. The effectiveness of the proposed techniques is verified with numerical examples.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1883-1887
• /
• 1991

Identification theory for linear discrete system has been presented by a great many reference, but research works for identification of continuous-time system are less than preceding identification. In fact, a great man), systems for engineering are continuous-time systems, hence, research for identification of continuous-time system has important meaning. This paper offers the following results: 1. Corresponding relations for the parameters of continuous-time model and discrete model may be shown, when single input-output system has general characteristic roots. 2. To do identification of single variable continuity linear system with stability constraints from samples of input-output data, it is necessary to use optimization with stability constraints. 3. Main results of this paper may be explained by a simple example.

• Environmental and Resource Economics Review
• /
• v.14 no.4
• /
• pp.839-866
• /
• 2005

This study addresses the effects on the economy of atomic sector's R&D by considering how much KAERI's R&D expenditures in 2000 affect on the production and value-added of each industry and the whole economy. This study answers to the question using competitive import input-output tables and both supply driven and demand driven IO models, which are frequently employed in evaluating economic impacts of R&D in both domestic and foreign academic areas.

• Journal of Korean Society of Rural Planning
• /
• v.15 no.2
• /
• pp.69-80
• /
• 2009

The purpose of this paper is to estimate the regional economic impact of reverse mortgage system based on farmer's net asset of house and farmland together. The regional economic impact was estimated by using inter-regional input-output model. Major findings are as follows: 1) The result of input-output analysis shows that 49,130 million won of production effect, 20,040 million won of value added effect, and 24,759 number of employment effect, 2) Since the result shows that the elderly spend most of the reverse mortgage money for their living expenses, it seems necessary to adopt net asset based reverse mortgage system to improve and stabilize farmers' living conditions and regional economy.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.1
• /
• pp.188-197
• /
• 2012

DEA 모델중 널리 사용되는 교차평가모델(cross efficiency model)은 가중치에 제한을 두지 않고 어떤 특정분야에 탁월한 성과를 내는 DMU(Decision Making Unit)보다는 보다 전반적인 분야에서 두각을 나타내는 DMU를 선발함으로써 많은 연구자들이 DEA문헌에서 적용하여 왔다. 본 연구에서는 이러한 교차평가모델이 실제에 있어서는 암묵적으로 고정 가중치를 사용한다는 것과 동일한 결과를 나타낸다는 것을 분석적으로 밝혔다(one input, multi output case). 또한 multi-input, multi-output case의 경우에도 overall performer의 cluster에 근접한 대다수 DMU의 경우에는 고정 가중치를 사용한 경우와 거의 차이가 없음을 보였다. 교차평가 모델에 적용된 변수의 가중치를 보다 명확히 함으로써 연구자들이 모델의 평가결과를 이해하는데 도움이 될 수 있을 것이다. 또한 교차 평가의 가중치 도식을 더 명확히 보여주기 위해 biplot을 제안한다.

• Management & Information Systems Review
• /
• v.5
• /
• pp.81-101
• /
• 2000

The purpose of this comparative study is to compare and evaluate venture business of electronic and communication industry by Data Envelopment Analysis(DEA). DEA is a linear programming-based technique that converts multiple input and output measures into a single comprehensive measures of productive efficiency. In this paper, the CCR model and trend analysis model are used to examine the efficiency of 18 venture business. Input variables are number of employees. raw-material costs and production capability and output variables are real production, sales revenues and net income after taxes. DEA approach broad information like as efficiency level of each Decision Making Unit(DMU), reference group of efficiency improvement and trends of efficiency shift. Finally, the correlation of input and output variables are examined to examine the relationship among variables.

• Proceedings of the KIEE Conference
• /
• 1999.07f
• /
• pp.2712-2714
• /
• 1999

The small signal model for input series-output parallel connected converter system employing charge control together with input capacitor voltage feedback loop is developed. From the model developed, the effect of input capacitor voltage feedback loop to the system stability and outer loop compensator design is analyzed. Theoretical results and simulation show that input capacitor voltage feedback loop has no critical effects on the system stability, so the system can be reduced to a equivalent single module for the stability analysis and outer loop compensator design.

• International journal of advanced smart convergence
• /
• v.4 no.1
• /
• pp.45-53
• /
• 2015

This paper is proposed mathematical load modelling based on system identification approach of energy consumption of residential air conditioning. Due to air conditioning is one of the significant equipment which consumes high energy and cause the peak load of power system especially in the summer time. The demand response is one of the solutions to decrease the load consumption and cutting peak load to avoid the reservation of power supply from power plant. In order to operate this solution, mathematical modelling of air conditioning which explains the behaviour is essential tool. The four type of linear model is selected for explanation the behaviour of this system. In order to obtain model, the experimental setup are performed by collecting input and output data every minute of 9,385 BTU/h air-conditioning split type with $25^{\circ}C$ thermostat setting of one sample house. The input data are composed of solar radiation ($W/m^2$) and ambient temperature ($^{\circ}C$). The output data are power and energy consumption of air conditioning. Both data are divided into two groups follow as training data and validation data for getting the exact model. The model is also verified with the other similar type of air condition by feed solar radiation and ambient temperature input data and compare the output energy consumption data. The best model in term of accuracy and model order is output error model with 70.78% accuracy and $17^{th}$ order. The model order reduction technique is used to reduce order of model to seven order for less complexity, then Kalman filtering technique is applied for remove white Gaussian noise for improve accuracy of model to be 72.66%. The obtained model can be also used for electrical load forecasting and designs the optimal size of renewable energy such photovoltaic system for supply the air conditioning.