• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.333-333
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• 2000

When the generalized singular perturbation method is used for model reduction, the state variables of the original system is reconstructed from the reduced order model. The state reduction error is defined, which shows how well the reconstructed state variables approximate the state variables of the original system equation.

• Journal of the Korean Home Economics Association
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• v.38 no.12
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• pp.111-129
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• 2000

The purpose of this study is to investigate the level of consumer instantly impulse buying in cuber market user. Also this study analyzes causal effect on consumer instantly impulse purchasing by demographic and social, place and promotion, consumer emotion state, and consumer internal and psychological variables. The data had been collected from on-line research method with 1,034, as using cuber market. The major statistical methods used for data analysis are frequency, percentile, mean, factor analysis, multiple regression analysis, Pearson's correlation analysis, and path analysis. The result of causal effect analysis were as follows; First, the variables affecting possession oriented materialism were sex and age. Second, the variables affecting self-control were sex, income, account of credit card, and instantly state of mind. Third, variables directly affecting instantly impulse purchasing were serif employed, banner advertisement, experience of cuber shopping, shopping mall pattern, instantly state of mind, purpose of shopping, happiness and success oriented materialism, and self-control. Also sex, income account of credit card, and instantly state of mind emerge to indirectly effect via self-control. Especially, the variables of success oriented materialism and instantly state of mind influenced on the highest of relative variables in consumer instantly impulse purchasing.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.555-558
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• 1991

The IESF(Integral Error and State Feedback) controller, which incorporates state feedback as a modern control scheme and integral action as a classical control scheme, has better performance than that of the conventional PID controller in linear time-invariant systems. The IESF controller requires the measurement of all the state variables. But, unfortunately, it may be difficult or impossible to measure all state variables in many applications. And the IESF controller is applicable only to pole-assignable linear time-invariant system without time delay. In this paper, new IESF controller structure was proposed which performs feedback with only measurable state variables. In order to estimate the unmeasurable state variables. It was adopted the filter mode by full-order obserber. The good performance and effectiveness of the proposed controller was confirmed by computer simulation.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.4
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• pp.462-467
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• 2007

The design and synthesis of a state feedback controller assumes the feedback of all state variables of the system. However, some state variables are not physical quantifies so that sensors may not be available, or may be too expensive to measure. Hence, a state observer can be an alternative to estimate unmeasurable state variables. This paper therefore presents a scheme for state observer-based stabilization control of inverted pendulum systems. The feedback gain matrices of both the state feedback controller and the state observer are tuned by real-coded genetic algorithms(RCGAs) such that the given performance indices are minimized. The proposed method is demonstrated through simulations.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.7
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• pp.773-783
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• 1992

There have been several control schemes for the single input systems with unmeasurable state variables using variable structure control(VSC) theory. However, each of them is a study on the systems which can be represented in the phase canonical form or non-phase canonical form dynamic equation separately. As these control algorithms have difficulties in practical application by its theoretical limitations, in this paper we propose a new VSC theory which overcomes those limitations, in this paper we propose a new VSC theory which overcomes those limitations of proposed schemes. This new control scheme can be realized for the general linear systems which have unmeasurable state variables. And the switching function of this VSS algorithm consists of measurable state variable function(reduced-order switching function) and its derivatives. Also in the construction of control imput only measurable state variables are used.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.595-602
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• 2008

In this paper, performance of the initial alignment for INS whose attitude is not leveled is investigated. Observability of the initial alignment filter is analyzed and estimation errors of the estimated state variables are derived. First, the observability is analyzed using the rank test of observability matrix and the normalized error covariance of the Kalman filter based on the 10-state model. In result, it can be seen that the accelerometer biases on horizontal axes are unobservable. Second, the steady-state estimation errors of the state variables are derived using the observability equation. It is verified that the estimates of the state variables have errors due to the unobservable state variables and the non-leveling tilt angles of a vehicle containing the INS. Especially, this paper shows that the larger the tilt angles of the vehicle are, the larger the estimation errors corresponding to the sensor biases are. Finally, it is shown that the performance of the 8-state model excepting the accelerometer biases on horizontal axes is better than that of the 10-state model in the initial alignment by simulation.

• Journal of Korean Elementary Science Education
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• v.40 no.3
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• pp.343-365
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• 2021

The purpose of this study was to clarify the effect of learner variables on triggering state curiosity and state anxiety in confronting scientific task situation for fifth to sixth grades of elementary school. Science curiosity, interest, need for cognition, science self-concept, science anxiety, prior knowledge, and perceived difficulty were selected as learner variables that are expected to affect state curiosity and state anxiety. As a result of this study, the variables that had a significant influence on evoking state curiosity in confronting scientific task situation were in the order of interest, need for cognition, science curiosity, and prior knowledge, and all of these variables had a positive effect. In addition, the variables that significantly affect on evoking state anxiety in confronting scientific task situation were in the order of science anxiety, perceived difficulty, need for cognition, science self-concept, and prior knowledge. Of these, only prior knowledge had a negative effect on evoking state anxiety, and the other variables had a positive effect. The results of this study are expected to broaden the comprehension of students' emotional states in science education, and provide a theoretical foundation for the studies of state curiosity and state anxiety in science learning.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.4
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• pp.136-145
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• 1998

This paper describes the FFT and coefficient analysis of vibration signals for preventive diagnosis of a mold transformer at normal and abnormal state. Varying applied voltage, loading current and temperature as control variables for he experiment, measurement variables such as magnitude of vibration signals, frequency spectrum and time series coefficient were analyzed. The vibration signals by variation of control variables were measured by acceleration sensor adhered on the surface of winding and core, and measurement variables were calculated using dat acquisition system. After analyzing the normal state, the structural distortion was also simulated. The vibration signals at abnormal state were measured by the same control variables variation as the normal state. As a result, vibration signals between normal and abnormal state could be distinguished by comparison of the perpendicular and horizontal vibration signal.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.419-424
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• 2012

This paper discusses the state-of-the-art techniques in real-time state estimation for the Smart Microgrids. The most popular method used in traditional power system state estimation is a Weighted Least Square(WLS) algorithm which is based on Maximum Likelihood(ML) estimation under the assumption of static system state being a set of deterministic variables. In this paper, we present a survey of dynamic state estimation techniques for Smart Microgrids based on Belief Propagation (BP) when the system state is a set of stochastic variables. The measurements are often too sparse to fulfill the system observability in the distribution network of microgrids. The BP algorithm calculates posterior distributions of the state variables for real-time sparse measurements. Smart Microgrids are modeled as a factor graph suitable for characterizing the linear correlations among the state variables. The state estimator performs the BP algorithm on the factor graph based the stochastic model. The factor graph model can integrate new models for solar and wind correlation. It provides the Smart Microgrids with a way of integrating the distributed renewable energy generation. Our study on Smart Microgrid state estimation can be extended to the estimation of unbalanced three phase distribution systems as well as the optimal placement of smart meters.

• Journal of Distribution Science
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• v.22 no.3
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• pp.59-70
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• 2024

Purpose: This study aimed to develop a strategic business conceptual model for large state plantations in West Java Province and Banten Province, Indonesia. The model was built through causal relationships and interrelationships between marketing strategies and business strategies that affect business performance on large state plantations. The plantation sector provides the largest contribution to gross domestic product and is an important part of national food distribution efforts. Research design, data, and methodology: This study used a literature review adapted from Pret and Logan (2019), which followed the guidelines of Tranfield et al. (2003), derived from the Scopus website with Q1/Q2 quartiles and inclusion/exclusion criteria published from 2012 to 2021. Results: Based on a systematic literature review approach, we constructed the strategic business conceptual model for large state plantations based on a combination of four causal and interrelationship variables that affect business performance, namely, industry attractiveness, unique capabilities, innovation management, and collaboration strategy. Conclusions: This research explains the relationship between industry attractiveness variables and unique capability as independent variables that can affect business performance through collaboration strategy and innovation management as intervening variables in the plantation sector, especially large state plantations, which have not been found in previous studies.