• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.511-518
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• 2013

To implement an automatic picking system (APS) in distribution center with high precision and high dynamics, this paper presents a design of a linear induction motor (LIM) drive and robust position controller based on integral variable structure control (IVSC) scheme. The force disturbance as well as the mechanical parameter variation such as the mass and friction coefficient gives a direct influence on the position control performance of APS. To guarantee a robust control performance in the presence of such uncertainty, a robust position controller is designed. A Simulink library is developed for the LIM model from the state equation. Through this model and comparative simulation based on Matlab - Simulink, it is proved that the proposed scheme has a robust control nature and is most suitable for APS.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.353-363
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• 2020

Hydrologic models can be classified into two types: those for understanding physical processes and those for predicting hydrologic quantities. This study deals with how to use the model to predict today's stream flow based on the system's knowledge of yesterday's state and the model parameters. In this regard, for the model to generate accurate predictions, the uncertainty of the parameters and appropriate estimates of the state variables are required. In this study, a relatively simple hydrologic partitioning model is proposed that can explicitly implement the hydrologic partitioning process, and the posterior distribution of the parameters of the proposed model is estimated using the Markov chain Monte Carlo approach. Further, the application method of the ensemble Kalman filter is proposed for updating the normalized soil moisture, which is the state variable of the model, by linking the information on the posterior distribution of the parameters and by assimilating the observed steam flow data. The stochastically and recursively estimated stream flows using the data assimilation technique revealed better representation of the observed data than the stream flows predicted using the deterministic model. Therefore, the ensemble Kalman filter in conjunction with the Markov chain Monte Carlo approach could be a reliable and effective method for forecasting daily stream flow, and it could also be a suitable method for routinely updating and monitoring the watershed-averaged soil moisture.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.57-66
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• 2009

수학적 모델은 수량과 수질의 예측을 위해 현장 조사의 대안으로 사용되어지며 이러한 모델의 사용과 실측에 불확실성이 존재하게 된다. 불확실성에 대한 많은 연구들이 진행되어 왔으나 시나리오에 의한 모델링 과정에서 발생하는 불확실성에 대한 연구는 미흡한 실정이다. 본 연구에서는 산림이 농경지와 목초지로의 변화에 따른 시나리오를 설계한 후 시나리오 적용에 따른 SWAT (Soil and Water Assessment Tool) 매개변수의 불확실성을 분석하고자 하였다. 몬테카를로 기법 (Monte Carlo simulation)을 이용하여 각 매개변수별 1,000개의 난수를 발생하였으며 앙상블 유량모의 기법을 이용하여 미국 Alabama주 카하바강 상류 (50,967ha)를 대상으로 각 난수별 100개의 유량을 통해 불확실성을 분석하였다. 분석 결과 산림지역이 농경지와 목초지로 변화 되었을 때 유출량이 증가하는 것으로 분석되었으며, 임야가 목초지 보다 농경지로 변화되었을 때 유출량은 더욱 증가하는 것으로 나타났다. 각 시나리오별 SWAT 매개변수의 불확실성은 AWC (Available water capacity), CN (Curve number), GWREVAP (groundwater re-evaporation coeffeicient), REVAPMN (minimum depth of water in shallow aquifer for re-evaporation to occur)순으로 크게 나타났으며, Ksat (Saturated hydraulic conductivity)와 ESCO(Soil evaporation compensation factor)는 유출량의 변화에 큰 영향을 미치지 못하는 것으로 분석되었다. 토지피복별 산림 면적이 클 경우 불확실성이 크게 나타나 산림이 목초지와 농경지로 변함에 따라 불확실성은 감소하는 것으로 나타났다.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.31 no.2
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• pp.178-189
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• 1995

In this pater, authors derive the state - space equiation about the patallel - type inverted pendulum which is adopted as control object, and constitute the control system by $H_\infty$control theory. The modeling error is unavoidably existed by linearization error, and so on. We regard this modeling error which is determined from the identification through frequency response as unstructured model uncertainty. An augmented state - space equiation with frequency weighting function is constructed for application of the $H_\infty$theory, and the mixed sensitivity problem is considered. The weighting functions are determined in consideration of the model uncertainty and the response of system in frequency region. The $H_\infty$controller is designed by using software package for controller design. From results of response simulation, the control system designed with $H_\infty$theory guarantees low sensitivity for disturbance as well as robustness against the model uncertainties.

• Steel and Composite Structures
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• v.51 no.1
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• pp.25-41
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• 2024

The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence of several suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (ANFIS) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (FHO) and equilibrium optimizer (EO) with the ANFIS, referred to as ANFIS_FHO and ANFIS_EO, respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that ANFIS_FHO and ANFIS_EO both have amazing potential for precisely calculating pile bearing capacity. The R² values obtained for ANFIS_FHO were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the ANFIS_FHO system had less uncertainty than the ANFIS_EO model. The research found that the ANFIS_FHO model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.

• Structural Engineering and Mechanics
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• v.90 no.1
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• pp.19-26
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• 2024

In recent years, an increasing number of experimental studies have shown that the practical application of mature active control systems requires consideration of robustness criteria in the design process, including the reduction of tracking errors, operational resistance to external disturbances, and measurement noise, as well as robustness and stability. Good uncertainty prediction is thus proposed to solve problems caused by poor parameter selection and to remove the effects of dynamic coupling between degrees of freedom (DOF) in nonlinear systems. To overcome the stability problem, this study develops an advanced adaptive predictive fuzzy controller, which not only solves the programming problem of determining system stability but also uses the law of linear matrix inequality (LMI) to modify the fuzzy problem. The following parameters are used to manipulate the fuzzy controller of the robotic system to improve its control performance. The simulations for system uncertainty in the controller design emphasized the use of acceleration feedback for practical reasons. The simulation results also show that the proposed H∞ controller has excellent performance and reliability, and the effectiveness of the LMI-based method is also recognized. Therefore, this dynamic control method is suitable for seismic protection of civil buildings. The objectives of this document are access to adequate, safe, and affordable housing and basic services, promotion of inclusive and sustainable urbanization, implementation of sustainable disaster-resilient construction, sustainable planning, and sustainable management of human settlements. Simulation results of linear and non-linear structures demonstrate the ability of this method to identify structures and their changes due to damage. Therefore, with the continuous development of artificial intelligence and fuzzy theory, it seems that this goal will be achieved in the near future.

• Smart Media Journal
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• v.1 no.1
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• pp.58-63
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• 2012

It is a superordinate concept to a network control system which optimally distributes the battery power to overall length parts through the linkage control drive and absorbs/integrates network diagnostics and overlapped functions with overall length control systems. This study is to develop a system that maximize the battery power and motor effectiveness by controlling motor battery controlling module with common MCU Integration linkage controlling system, and to develop S/W and H/W that can be controlled by linked with each controlling module in CAN method through using Autosar's standardized software.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1816-1819
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• 1997

Using the vision system, robotic tasks in unstructured environments can be accompished, which reduces greatly the cost and steup time for the robotic system to fit to he well-defined and structured working environments. This paper proposes a dynamic control scheme for robot manipulator with eye-in-hand camera configuration. To perfom the tasks defined in the image plane, the camera motion Jacobian (image Jacobian) matrix is used to transform the camera motion to the objection position change. In addition, the dynamic learning controller is designed to improve the tracking performance of robotic system. the proposed control scheme is implemented for tasks of tracking moving objects and shown to outperform the conventional visual servo system in convergence and robustness to parameter uncertainty, disturbances, low sampling rate, etc.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.45-53
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• 1997

This paper presents hybrid expert system for diagnosis of electric power transformer faults. The expert system diagnose and detect faults in oil-filled power transformers based on dissolved gas analysis. As the preprocessing stage, fuzzy information theory is used to manage the uncertainty in transformer fault diagnosis using dissolved gas analysis. The Kohonen neural network takes the interim results by applying fuzzy informations theory as inputs, and performs the transformer fault diagnosis. The Proposed system tested gas records of power transformers from Korea Electric Power Corporation to verify the diagnosis performance of transformer faults.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.117-122
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• 2007

Recently, as the management environments are changing rapidly and the uncertainty is becoming larger, the needs of internal control for management and IS become stronger. In order to construct a new internal control system for IS, it is necessary to evaluate the former research of the system. This study emphasizes the importance of effective internal control system, presents a conceptual framework for the preceding factors to consider, and verifies empirically the framework. This study sets the organization citizenship behavior, IS innovation resistance, and IT capability from the viewpoint of Socio-Technical system as the preceding factors for the effectiveness of internal control system. A research model, affecting the above factors on IS capability as a mediating variable of the internal control effectiveness for the use of IS, is set up. PLS-Graph 3.0 is used to verify the model. We found that the internal control effectiveness have affirmative effect on information capability, a surrogate variable of the IS effectiveness and a mediation effect is meaningful.