• 전기학회논문지
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• 제56권9호
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• pp.1665-1675
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• 2007

This paper presents the problem of controlling asynchronous sequential machines in the presence of input disturbances, which may be also regarded as an adversary in a game theoretic setting. The main objective is to provide necessary and sufficient condition for the existence of a corrective controller that solves model matching problem of an asynchronous machine suffering from input disturbance. The existence condition can be stated in terms of a simple comparison of two skeleton matrices. The proposed controller eliminates the adversarial effect of input disturbance and makes the controlled machine mimic the behavior of a model in stable-state way. Whenever controller exists, algorithms for their design are outlined and demonstrated in a case study.

• 제어로봇시스템학회논문지
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• 제12권6호
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• pp.547-553
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• 2006

This paper studies digital control of biodynamic model of HIV-1 via intelligent digital redesign (IDR). The purpose of the IDR is to develop an equivalent digital fuzzy controller maintaining the satisfactory performance of an existing continuous-time fuzzy controller in the sense of the state-matching. Some conditions for the stability as well as the global state-matching are provided.. They are given by the form of the linear matrix inequalities (LMIs) and thereby easily tractable by the convex optimization techniques. The main features of the proposed method are that 1) the generalized control scheme is provided for the multirate as well as the single-rate digital controllers; 2) a new compensated block-pulse function method is applied to closely match the states of the continuous-time and the sampled-data fuzzy systems in the discrete-time domain; 3) the two-step procedure of IDR is presented to prevent the performance degradation caused by the additional stability conditions. The applicability of the proposed approach is shown through the biodynamic model of HIV-1.

• 제어로봇시스템학회논문지
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• 제22권6호
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• pp.429-434
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• 2016

This paper introduces a stabilization condition for polynomial fuzzy systems that guarantees $H_{\infty}$ performance under the imperfect premise matching. An $H_{\infty}$ control of polynomial fuzzy systems attenuates the effect of external disturbance. Under the imperfect premise matching, a polynomial fuzzy model and controller do not share the same membership functions. Therefore, a polynomial fuzzy controller has an enhanced design flexibility and inherent robustness to handle parameter uncertainties. In this paper, the stabilization conditions are derived from the polynomial Lyapunov function and numerically solved by the sum-of-squares (SOS) method. A simulation example and comparison of the performance are provided to verify the stability analysis results and demonstrate the effectiveness of the proposed stabilization conditions.

• International Journal of Automotive Technology
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• 제8권3호
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• pp.299-308
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• 2007

This study proposes a two-layer hierarchical control system that integrates active front wheel steering and four wheel braking torque control to improve vehicle handling performance and stability. The first layer is a robust model matching controller (R-MMC) based on linear matrix inequalities (LMIs), which optimizes an active front steering angle compensation and a desired yaw moment control, and calculates reference wheel slip for the target wheel according to the desired yaw moment. The second layer is a moving sliding mode controller (MSMC) that can track the reference wheel slip in a predetermined time by commanding proper braking torque on the target wheel to achieve the desired yaw moment. Since vehicle sideslip angle measurement is difficult to achieve in practice, a sliding mode observer (SMO) that requires only vehicle yaw rate as the measured input is also developed in this study. The performance and robustness of the SMO and the integrated control system are demonstrated through comprehensive computer simulations. Simulation results reveal the satisfactory tracking ability of the SMO, and the superior improved vehicle handling performance, stability and robustness of the integrated control vehicle.

• Genomics & Informatics
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• 제17권4호
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• pp.47.1-47.12
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• 2019

The achievements of genome-wide association studies have suggested ways to predict diseases, such as type 2 diabetes (T2D), using single-nucleotide polymorphisms (SNPs). Most T2D risk prediction models have used SNPs in combination with demographic variables. However, it is difficult to evaluate the pure additive contribution of genetic variants to classically used demographic models. Since prediction models include some heritable traits, such as body mass index, the contribution of SNPs using unmatched case-control samples may be underestimated. In this article, we propose a method that uses propensity score matching to avoid underestimation by matching case and control samples, thereby determining the pure additive contribution of SNPs. To illustrate the proposed propensity score matching method, we used SNP data from the Korea Association Resources project and reported SNPs from the genome-wide association study catalog. We selected various SNP sets via stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and the elastic-net (EN) algorithm. Using these SNP sets, we made predictions using SLR, LASSO, and EN as logistic regression modeling techniques. The accuracy of the predictions was compared in terms of area under the receiver operating characteristic curve (AUC). The contribution of SNPs to T2D was evaluated by the difference in the AUC between models using only demographic variables and models that included the SNPs. The largest difference among our models showed that the AUC of the model using genetic variants with demographic variables could be 0.107 higher than that of the corresponding model using only demographic variables.

• 대한기계학회논문집A
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• 제29권4호
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• pp.570-577
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• 2005

In this study a complete 3D surface reconstruction method is proposed based on the concept that the vertices of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

• 제어로봇시스템학회논문지
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• 제8권7호
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• pp.589-598
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• 2002

The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.518-523
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• 2002

Nowadays the Rational Function Model (RFM), an abstract sensor model, is substituting physical sensor models for highly complicated imaging geometry. But RFM is algorithm to be required many Ground Control Points (GCP). In case of RFM of the third order, At least forty GCP are required far RFM generation. The purpose of this study is to research more efficient algorithm on GCP and accurate algorithm similar to RFM. The Polynomial Camera Model is relatively accurate and requires a little GCP in comparisons of RFM. This paper introduces how to generate Polynomial Camera Model and fundamental algorithms for construction of 3-D topographic data using the Polynomial Camera Model information in the Kompsat stereo pair and describes how to generate the 3-D ground coordinates by manual matching. Finally we tried to extract height information for the whole image area with the stereo matching technique based on the correlation.

• 제어로봇시스템학회논문지
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• 제20권6호
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• pp.606-611
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• 2014

The understanding of another's behavior is a fundamental cognitive ability for primates including humans. Recent neuro-physiological studies suggested that there is a direct matching algorithm from visual observation onto an individual's own motor repertories for interpreting cognitive ability. The mirror neurons are known as core regions and are handled as a functionality of intent recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper, we addressed previous works used to model the function and mechanisms of mirror neurons and proposed a computational model of a mirror neuron system which can be used in human-robot interaction environments. The major focus of the computation model is the reproduction of an individual's motor repertory with different embodiments. The model's aim is the design of a continuous process which combines sensory evidence, prior task knowledge and a goal-directed matching of action observation and execution. We also propose a biologically inspired plausible equation model.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.401-406
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• 2004

In this paper, a new time-domain adaptive predistortion scheme is proposed to compensate for the nonlinearity of high power amplifiers (HPA) in OFDM systems. A complex Wiener-Hammerstein model (WHM) is adopted to describe the input-output relationship of unknown HPA with linear dynamics, and a power series model with memory (PSMWM) is used to approximate the HPA expressed by WHM. By using the PSMWM, the compensation input to HPA is calculated in a real-time manner so that the linearization from the predistorter input to the HPA output can be attained even if the nonlinear input-output relation of HPA is uncertain and changeable. In numerical example, the effectiveness of the proposed method is confirmed and compared with the identification method based on PSMWM.