• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.509-512
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• 1995

A new modeling incorporating the role of control arm is proposed for the Macpherson type suspension system. Vertical displacement of the sprung mass and angular displacement of the control arm are selected as main control variables in the new modeling. With the same values of suspension vehicle parameters the conventional modeling and the new modeling are compared in terms of open loop characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.558-561
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• 1993

The main difference between a linear system and a nonlinear system is the existence of direct interactions between input signals. These interactions will be classified into three types, (1) self-interaction among different order terms of control signals, (2) static mutual interactions between the control signals, and (3) dynamic interactions through the coefficient venctor fields of the control variables. In this paper, we will show that interactions of type (2) and (3) can be avoided by applying an appropriate dynamic compensator, while the interaction of type (1) is fatal.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.22-30
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• 1993

In this paper, robust adaptive control algorithms which can be applied to unknown uncertain systems are suggested. Transform matrix for dividing states into "uncontrolled" states and "controlled" states and general searching procedure for the transform matrix which assign arbitrary n-1 eigen values for the uncontrolled subsystem of n-th orther single-input single-output systems of which state variables can be observable are also studied and utilized for the design of new-type controllers. We drived new-type control laws by using adaptive control theory and variable structure system and its stability is proved by using Lyapunov stability theory.

• Korean Journal of Health Education and Promotion
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• v.18 no.3
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• pp.11-36
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• 2001

The purpose of this study is to analyze health behavior by comparing the difference between self-perceived health status and health examination results. The study subjects consist of 7,702 people aged over 20, surveyed by Health Interview survey, Health Examination survey, Dietary Life survey, Health Consciousness and Behavior survey. Data used in the study are drawn from raw data from a 1998 National Health and Nutrition survey. General characteristics variables are sex, age, education level, residential area, marital status, occupation, and living standard while dichotomous variables, ‘not healthy’ and ‘healthy’ are used to measure self-perceived health status. Variables for health examination results are high blood pressure, high cholesterol, diabetes, liver diseases, liver inflammation, kidney diseases, normal weight, regular diet, optimum sleeping time(7-8 hours), regular health examination and health behavior practice group. Major findings of the study are as follows: 1) Analysis of self-perceived health status and health behavior by disease: Variables significantly correlated with high self-perceived health status have strong associations with high health behavior practice, which supports the hypothesis that as one has high self-perceived health status, one is more likely to practice health promoting behavior. The results of analysis of health behavior differences by dividing subjects into two categories, ‘cases of illness’ and ‘cases of no illness’ indicate that drinking, sleeping time, health examination are significant variables (p〈0.001, 0.05) whereas smoking, weight control, regular exercise, regular diet are not significant. 2) Analysis of disparity patterns between self-perceived health status and health examination: The hypothesis that health behaviors would be different according to the disparity pattern between self-perceived health status and health examination is supported as a result of χ2 test. Among Type I : Self-perceived health status is high and actual health status is good (no disease) Type II: Self-perceived health status is high and actual health status is poor(have disease) Type III: Self-perceived health status is low and actual health status is good(no disease) Type IN: Self-perceived health status is low and actual health status is poor(have disease) Type I and Type IV show no disparity, Type I shows the highest health promoting behavior whereas Type IV shows the lowest health promoting behavior. Type II, and III, compared to Type I, practise lower health promoting behavior. Multi-logistics regression analysis was conducted to find out the degree of impact on health behavior. Independent variables are general characteristics, self-perceived health status and health examination result and presence of illness, while the dependent variable is health promoting behavior. The analysis of the impact of self-perceived health status on the health promoting behavior shows that smoking, drinking, weight control, regular exercise, health examination practice, and/or regular diet are significantly correlated to self-perceived health status. High self-perceived health status is inversely related to high health promoting behavior. This finding supports the hypothesis that the higher one perceives one's health, the more likely one is to practice health promoting behavior. On the contrary, the presence of illness has little impact on health promoting behavior. 3) Multiple logistics analysis on how disparity patterns between self-perceived health status and health examination affect health behavior: The results of multiple logistics analysis made on health behavior variables compared to the standard variable are as follows: When analyzed on the standard of Type I, smoking is a significant risk factor for the Type IV. In case of drinking, all the patterns show a high probability of relative risk ratio. With regard to weight control, it is a risk factor for Type II while all the patterns show high probability of not practising when analyzed on the standard of type IV. Type III and IV show high probability of not doing regular exercise while Type IV, shows a high probability of not taking appropriate sleeping time. When analyzed on the standard of type IV, all the patterns show a high probability of not taking health examinations. Type III and IV show a high probability of not having regular meals. As for overall health promoting behavior, Type III and IV show a high relative risk ratio. These two groups have low self-perceived health status. It implies that self-perceived health status has significant impact on health promoting behavior. This is also supported by the fact that Type I with high self-perceived health status and no illness shows a high practice rate of health promoting behavior. Types II and III the groups with high disparity between self-perceived health status and health examination results, show a low practice rate of health promoting behavior when compared to Type I. Type IV, that is the group with low self-perceived health status and actual illness, shows the lowest practice of health promoting behavior. It is highly probable that this type proves to be the poorest health group.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.14-20
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• 1997

This paper proposes a new design method for the SMC-type FLC and shows that a SMC-type LFC is an extension of the SMC with BL. The conventional SMC-type FLC uses error and change-of-error as inputs of the FLC and generates the absolute value of a switching magnitude. Then, the fuzzy rule table is constructed on a two-dimensional space of the phase plane and has commonly the skew symmetric property. In this paper, we introduce a new variable, signed distance, from the skew symmetric property of the rule table. And thd variable becomes only a fuzzy variable that is used to generate the control input of a SMC-type FLC. that is, we design a new SMC-type FLC that uses a signed distance and a control input as the variables representing the contents of the rule-antecedent and the rule-con-sequent, respectively. Then the number of total rules is reduced and the control performance is almost the same as that of the conventional SMC-type FLC. Additionally, we derive the control law of the ordinary SMC with BL from a new SMC-type FLC. Namely, we show that a FLC is an extension of the SMC with BL.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.93.3-93
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• 2001

We propose the cascade PID type fuzzy control method for a good performance such as robustness. The one of proposed method, the first stage have two input variables of an error and a derivative error, and one output variable, and the next stage have two input variables of the output of first stage and an integral error, and one output variable, have two stages. The other, the first stage has one input of an error, and one output variable, and the second stage have two input of the output of first stage and a derivative error, and one output variable, and the third stage have two input of the output of the second stage and an integer error, and one output variable ...

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.8
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• pp.780-786
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• 2001

For the compressor speed control of a multi-type air conditioning system, a fuzzy control algorithm was developed. The sum of zone temperature errors and its derivative were used as input variables, and the compressor speed was selected as the output variable. To test the effectiveness of the control algorithm, one outdoor environmental chamber and four indoor environmental chambers were used. In the chambers the zone temperature step change test and the indoor unit change over test were performed. Test results showed that, for the control of compressor speed, the fuzzy control algorithm was more effective than the conventional proportional control algorithm for the energy conservation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.31-42
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• 1985

Thig paper used two feedback sensors, that is, potentiometer and tachometer in order to control DC motor. Also, the state feedback and kalman regular type in the linear system or the state feedback and on-off relay type in the non-linear system are used as control meth-ods for optimal control values. This compared and analyzed the control estimate of tracking angles by the estimate of three branches of methods of position and speed measured, position and speed by PD and position, speed and covariance by an observer.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.23 no.3
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• pp.245-255
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• 2016

Purpose: This study was conducted to compare self-care behaviors and self-care behavior related factors for groups of patients with good, inadequate and poor glycemic control. The study was based on variables of the Theory of Planned Behavior by Ajzen, habit and family support. (1991). Methods: Participants were 134 patients with type 2 diabetes (good glycemic control group: 57, inadequate glycemic control group: 40, poor glycemic control group: 37). Self-care behaviors, intention to self-care behavior and self-care behavior related variables (attitude, subjective norms, perceived behavior control, habits and family support) were measured. Data were collected from August 12 to September 25, 2014 and were analyzed using $x^2$-test, Fisher's exact test, ANCOVA, and logistic regression with SPSS/WIN 21.0. Results: Among the three glycemic groups, there were significant differences in self-care behavior, subjective norms, perceived behavior control, family support, and habits. Multinomial logistic regression showed that poor blood glucose probability was associated with duration of diabetes mellitus, method of DM therapy, perceived behavior control and habits. Conclusion: The study findings reveal the important role of self-care behavior, subjective norms, perceived behavior control, family support, and habits in blood glucose control in adults with type 2 diabetes.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.179.5-179
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• 2001

Generally, while PD-type fuzzy controller has good performance in transient period, it has uniform steady state error of response. To improve limitations of PD-type fuzzy controller, we propose a new fuzzy controller to improve the performance of transient response and to eliminate the steady state error of response. In this paper, PD-type fuzzy controller is used a simplified indirect inference method(SIIM). When the SIIM is applied, the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. The outputs of this controller are the output calculated by PD-type fuzzy controller and the accumulated error scaling factor. Here, the accumulated error scaling factor is adjusted by fuzzy rule according to the system state variables. To show the usefulness of the proposed controller, it is applied to 0-type 2nd-order linear system.