• Journal of Families and Better Life
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• v.7 no.1
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• pp.43-57
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• 1989

In the materialistic societies, individuals get money return according to the importance of their roles. But unlike wage workers who are engaged in market production , housewives engaged in home production do not get that return. It is because the result of home production is not transacted in the market and the price is not given to it, so the value of home production is not estimated. Hence this study trcognizes again the value of home production, suggests the estimation methods of it in input and output based on home production systems and attempts to actualize those methods socially. This home production develops the human attributes of family members to act as a member of a society and potentially contributes to home income and Gross National Products, so it has social and economic value. In spite of that significance, the value of home production is not estimated, so its nor recognized and housewives engaged in home production are not acknowledged their ability. Hence based on home production systems form input to output, this study suggested opportunity cost method and market cost method in input, method by saving money expenditure, hybrid method and method by comparing with market in output.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.7
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• pp.1247-1253
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• 2008

A design method of a T-S fuzzy model based reduced order nonlinear unknown input observer(NUIO) is presented. The fuzzy NUIO is designed based on the parallel distributed compensation(PDC) concept. It consists of a number of the linear UIOs, each of which is designed for each local linear model in the T-S fuzzy model of a class of nonlinear systems. The fuzzy NUIO provides not only the state estimates insensitive to the unknown inputs, for example, disturbances and faults etc., but also the estimates of the unknown inputs. Therefore, It can be employed in the state feedback control and disturbance rejection control of a class of nonlinear systems with unknown disturbances. It also applied to the robust residual generation for the fault detection and isolation systems and to the design of fault tolerant control systems. As an example, the NUIO is applied to an inverted pendulum system to show the state and disturbance estimation performance and to illustrate the fuzzy reduced order NUIO design method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.476-476
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• 2000

This paper deals with an estimation method far sideslip angle by using an unknown input observation technique in 4WS passenger car systems. Firstly, a 4WS vehicle model with 3DOP is derived under the constant velocity and same tyre's properties. The induced model is transformed into the linear state space model with considering the external disturbance. Secondly, an unknown input observer is introduced and its property which estimating the states of system without any disturbance information is shown. Lastly, the estimated sideslip angle of the 4WS system is verified through numerical simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.95-101
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• 2001

Most robust control schemes for stabilizing the systems with uncertainties require that the systems are satisfied with matching conditions. This paper is proposed to robust control using the time delay estimation for the nonlinear single input systems not satisfying the matching conditions. Synthetic input concept is used to design the control law. The unmatched uncertainties considered in this paper are more general than other studies and they need not a special form or information about their bound. We applied the proposed method to a single pendulum with a motor system.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.234-239
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• 2006

In this paper, we propose an interacting multiple model (IMM) method using intelligent tracking filter with fuzzy gain to reduce tracking errors for maneuvering targets. In the proposed filter, the unknown acceleration input for each sub-model is determined by mismatches between the modelled target dynamics and the actual target dynamics. After a acceleration input is detected, the state estimates for each sub-filter are modified. To modify the accurate estimation, we propose the fuzzy gain based on the relation between the filter residual and its variation. To optimize each fuzzy system, we utilize the genetic algorithm (GA). The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model(AIMM) method and input estimation (IE) method through computer simulations.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2006.11a
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• pp.328-333
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• 2006

A few methodologies have been recently developed to estimate the environmental affect when various materials and components are used in building life cycle. The direct survey method has limitations to analyze the environmental problems because of the limit of survey scope and cost. Therefore, another indirect method has been developed as alternatives. The indirect method is represented as input-output analysis. This paper aimed at analyzing the estimation the environmental affect of building materials and works at building construction, utilizing the input-output analysis as a indirect estimation method. The results suggested that the building works is overally responsible for the energy consumption and $CO_2$ emission. In other words, Over the 80% of the total consumption and $CO_2$ emission are resulted at the building work.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.114-120
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• 2000

Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification ＆ validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.4
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• pp.181-185
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• 2011

Due to the increasing of nonlinear loads such as converters and inverters connected to the electric power distribution system, and extensive application of harmonic generation sources with power electronic devices, disturbance of the electric power system and its influences on industries have been continuously increasing. Thus, it is difficult to construct accurate load model for active and reactive power in environments with harmonics. In this research, we develop current harmonics estimation method based on Extreme Learning Machine (ELM) with fast learning procedure for residential loads. Using data sets acquired from various residential loads, the proposed method has been intensively tested. As the experimental results, we confirm that the proposed method makes it possible to effective estimate current harmonics for various input voltage.

• Journal of Electrical Engineering and Technology
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• v.4 no.2
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.390-400
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• 2010

BNWF(Beam on Nonlinear Winkler Foundation) method has long been adopted for lateral behavior analysis of pile foundation and widely recognized for its simplicity and accuracy up until now. However, due to lateral load tests which were done in limited conditions and theory-based input Parameter estimation, the applicbility of p-y curve has not been fully examined. Accordingly, we researched on the applicability of conventional input parameter estimation and the p-y curve to be determined by the estimation through inverse analysis based on lateral load tests.