• Journal of IKEEE
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• v.23 no.4
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• pp.1265-1272
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• 2019

We analyze the robustness of the existing predictor feedback controller for discrete-time linear systems with constant input delays against the structured model uncertainty. By modeling the constant input delay with a first-order PdE (Partial difference Equation), we replace the input delay with the PdE states. By applying a backstepping transformation, we build a target system that enables to construct an explicit Lyapunov function. Constructing the explicit Lyapunov function that covers the entire state variables, we prove the existence of an allowable maximum size of the structured model uncertainty to maintain stability and establish the robustness of the predictor feedback controller. The numerical example demonstrates that the stability of closed-loop system is maintained in the presence of the structured model uncertainty, and verifies the robustness of the predictor feedback controller.

• Journal of Power Electronics
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• v.13 no.5
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• pp.814-828
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• 2013

The LCL resonant inductive power transfer (IPT) system is increasingly used because of its harmonic filtering capabilities, high efficiency at light load, and unity power factor feature. However, the modeling and controller design of this system become extremely difficult because of parameter uncertainty, high-order property, and switching nonlinear property. This paper proposes a frequency and load uncertainty modeling method for the LCL resonant IPT system. By using the linear fractional transformation method, we detach the uncertain part from the system model. A robust control structure with weighting functions is introduced, and a control method using structured singular values is used to enhance the system performance of perturbation rejection and reference tracking. Analysis of the controller performance is provided. The simulation and experimental results verify the robust control method and analysis results. The control method not only guarantees system stability but also improves performance under perturbation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1287-1292
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• 1999

In large-scale systems, we frequently encounter the time-delay and the uncertainty, and these should be considered in the design of controller because these are the source of the degradation of the system performance and instability of system. In this paper, we consider the robust stability of the linear large scale systems with the uncertainties and the time-delays. The considered uncertainties are both structured uncertainty and the unstructured uncertainty. Also, the considered time-delays are time-varying having finite time derivative limits. Based on the Lyapunov theorem and the linear matrix inequality(LMI) technique, we present two sufficient conditions that guarantee the robust stability of the system. The conditions are expressed as the LMI forms which can be easily checked their feasibility by using the well-known LMI control toolbox. Finally, we show by two examples that our results are less conservative than the previous results.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.4
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• pp.183-190
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• 2000

It is well-known that the poles of a system are closely related with the dynamics of the systems, and the pole assignment problem, which locates the poles in the desired regions, in one of the major problem in control theory. Also, it is always possible to assign poles to specific points for exactly known linear systems. But, it is impossible for the uncertain linear systems because of the uncertainties that originate from modeling error, system variations, sensing error and disturbances, so we must consider some regions instead of points. In this paper, we consider both the analysis and the design of robust pole assignment problem of linear system with time-varying uncertainty. The considered uncertainties are the unstructured uncertainty and the structured uncertainty, and the considered region is the circular region. Based on Lyapunov stability theorem and linear matrix inequality(LMI), we first present the analysis result for robust pole assignment, and then we present the design result for robust pole assignment. Finally, we give some numerical examples to show the applicability and usefulness of our presented results.

• Journal of Korean Academy of Nursing
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• v.45 no.2
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• pp.271-279
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• 2015

Purpose: This study was done to examine the relation of uncertainty, uncertainty appraisal, and self-management in patients undergoing hemodialysis, and to identify factors influencing self-management. Methods: A convenience sample of 92 patients receiving hemodialysis was selected. Data were collected using a structured questionnaire and medical records. The collected data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlations and multiple regression analysis with the SPSS/WIN 20.0 program. Results: The participants showed a moderate level of uncertainty with the highest score being for ambiguity among the four uncertainty subdomains. Scores for uncertainty danger or opportunity appraisals were under the mid points. The participants were found to perform a high level of self-management such as diet control, management of arteriovenous fistula, exercise, medication, physical management, measurements of body weight and blood pressure, and social activity. The self-management of participants undergoing hemodialysis showed a significant relationship with uncertainty and uncertainty appraisal. The significant factors influencing self-management were uncertainty, uncertainty opportunity appraisal, hemodialysis duration, and having a spouse. These variables explained 32.8% of the variance in self-management. Conclusion: The results suggest that intervention programs to reduce the level of uncertainty and to increase the level of uncertainty opportunity appraisal among patients would improve the self-management of hemodialysis patients.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.11-15
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• 1999

In this paper, a robust pole placement controller for time invariant linear systems with polytopic uncertainties is presented. The proposed controller is a fixed order output feedback controller which stabilizes the uncertain systems and satisfies the constraints on the closed-loop pole location. The proposed controller can be obtained by minimizing a certain nonlinear object function subject to linear matrix inequality constraints. An algorithm for solving the nonlinear optimization problem is also proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.923-931
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• 1999

In this paper, a modeling and a robust time-delay control for the reclaimer are investigated. Supplying the same amount of a raw material throughout the reclamation process from the raw yard to a sinter plant is important to keep the quality of the molten steel uniform in blast furnaces. As the actual parameter values of the reclaimer are not available, the boom rotational dynamics are modeled as a second order differential equation with unknown coefficients. The unknown parameters in the nominal model are estimated using a recursive estimation method. Another important factor in the control design of the reclaimer is the large time-delay in output measurement. Assuming a multiplicative uncertainty, that accounts for both the unstructured uncertainty neglected in the modeling and the structured uncertainty contained in the parameter estimation, a robust Smith predictor is designed. A robust stability criterion for the multiplicative uncertainty is also derived. Following the work of Goodwin et al. [4], a quantifying procedure of the multiplicative uncertainty bound, through experiments , is described. Experimental and simulation results are provided.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.24 no.1
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• pp.61-68
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• 2017

Purpose: The purpose of this study was to understand how disease activity and uncertainty influence anxiety and depression in patients with ankylosing spondylitis Methods: Participants were 125 patients with ankylosing spondylitis who had attended the rheumatology division of a university hospital. A structured questionnaire was used to assess disease activity, uncertainty, anxiety, and depression. The data gathered were analyzed using t-tests, ANOVAs, Pearson correlation coefficients, and a multiple regression. Results: Differences were observed in anxiety based on job status, and in depression based on age, marriage, and job status. Uncertainty and disease activity predicted patients' anxiety and explained 40% of the variance in this measure, and the relative influence of uncertainty (${\beta}=.38$, p<.001) was larger than that of disease activity (${\beta}=.30$, p<.001). Furthermore, uncertainty and disease activity predicted depression and explained 36% of the variance therein, and the relative influence of uncertainty (${\beta}=.27$, p=.002) and disease activity (${\beta}=.27$, p=.003) was similar. Conclusion: This study confirmed that disease activity and uncertainty influenced anxiety and depression in patients with ankylosing spondylitis. Therefore, efforts to decrease anxiety and depression in patients with this condition must take into consideration disease activity when implementing nursing interventions and should include strategies to lower uncertainty.

• Women's Health Nursing
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• v.13 no.4
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• pp.290-298
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• 2007

Purpose: This study was to measure the quality of life(QOL) and to identify the related factors in gynecological cancer patients during chemotherapy. Method: The subjects of this study were the patients who had undergone a hysterectomy and were admitted for chemotherapy at S university hospital between November 2006 and April 2007. Data was collected from 106 gynecological cancer patients with the use of a structured questionnaire which measured the QOL(FACT-G), body image, the presence of anxiety & depression, uncertainty, and family support. The data was analyzed by the SPSS win 12.0 program. Results: The mean FACT-total score was 62.1$({\pm}16.7)$ (range; 26-107). Positive correlations were found between QOL and body image(r= .67, p= .00), and QOL and family support(r= .32, p= .00), whereas there were negative correlations between QOL and anxiety(r= -.54, p= .00), QOL and depression(r= -.70, p= .00), and QOL and uncertainty(r= -.59, p= .00). Fifty seven pre cent of the variance in subjective overall QOL can be explained by depression, body image, and uncertainty(Adj $R^2$= .57, F=47.00, p= .00). Conclusion: Our patients had a relatively low QOL score. Factors significantly affecting quality of life were depression, body image and uncertainty. Nursing interventions, therefore, should be focused on improving QOL in gynecological cancer patients during chemotherapy, particularly so in patients with depression, uncertainty or poor body image.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.351-354
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• 1993

In this paper, reheat-fan engine is described as class of models constructed from nominal and uncertainty model for robust control. In this class of models, uncertainty model consists of structured and unstructured uncertainty, and each model is identified from nonlinear simulation using FFT and ML technique. Then, control requirements and augmented plant are specified. H$_{\infty}$ controller satisfying the control requirements is designed by using constant scaling matrix. Finally, efficacy of the H$_{\infty}$ controller is showed by computer simulation.n.