• Convergence Security Journal
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• v.14 no.7
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• pp.45-51
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• 2014

The most important point in the QoS management system to ensure the quality of the IoT system design goal is quality measurement system and the quality evaluation system. This research study is a matrix model for the IoT based on key quality measures by diagnosis system structure and function. Developing for the quality metrics measured Internet of Things environment will provide the foundation for the Internet of Things quality measurement/analysis. IoT matrix system for quality evaluation is a method to describe the functional requirements and the quality requirements in a single unified table for quality estimation performed. Comprehensive functional requirements and quality requirements by assessing the association can improve the reliability and usability evaluation. When applying the proposed method IoT quality can be improved while reducing the QoS signaling, the processing, the basis for more efficient quality assurances as a whole.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.560-570
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• 1999

This paper formulates the suboptimal robust Kalman filtering problem into two coupled Linear Matrix Inequality (LMI) problems by applying Lyapunov theory to the augmented system which is composed of the state equation in the uncertain linear system and the estimation error dynamics. This formulations not only provide the sufficient conditions for the existence of the desired filter, but also construct the suboptimal robust Kalman filter. The proposed filter can guarantee the optimized upper bound of the estimation error variance for uncertain systems with parametric uncertainties in both the state and measurement matrices. In addition, this paper shows how the problem of finding the minimizing solution subject to Quadratic Matrix Inequality (QMI), which cannot be easily transformed into LMI using the usual Schur complement formula, can be successfully modified into a generic LMI problem.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.892-895
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• 1996

An unknown input observer is proposed that can be used in wheelbase preview control of commercial vehicles. The preview and state information, required to calculate actuator force, are reconstructed from the measurement variables such as heave and pitch acceleration. Gain matrix of observer is optimally selected so that influence of system and measurement noises on the estimation error can be minimized. Estimated preview information requires low pass filtering to eliminate high frequency components resulting from differentiation of noisy output signals. Effectiveness of the proposed method is demonstrated by numerical simulation of half car model.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.106-112
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• 1999

This paper presents an H$\infty$ controller design method for linear systems with time-varying delayed states, inputs, and measurement outputs. Using a Lyapounov unctional , the stability for delay systems is discussed independently of time delays . And a sufficient condition for the existence of H$\infty$ controllers of n-th order is given in terms of three matrix inequalities. Based on the positive-definite solutions of their matrix inequalities, we briefly explain how to construct H$\infty$ construct H$\infty$ controller, which stabilizes time-delay systems independently of delays and guarantees an H$\infty$ norm bound.

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.851-856
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• 2008

Construction of large-scale container ports with the productivity improvements in container cranes shortened time of staying port to increase the level of service it harbors efforts accelerated. About container crane system exerted on the input, which is designed to look good performance considering the states feedback control system. The states observer designed of container cranes state variables that are expected to measurement noise or particular measurement signal. In the status of existing research, the feedback gain matrix and the state observer gain matrix are searched by being separated solving. But the feedback gain matrix and the state observer gain matrix are searched by RCGAs at once that be used robust search method in this paper.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.411-416
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• 2016

This paper presents the design methodology of an unknown input observer for Lipschitz nonlinear systems with unknown inputs in the framework of convex optimization. We use an unknown input observer (UIO) to consider both nonlinearity and disturbance. By deriving a sufficient condition for exponential stability in the linear matrix inequality (LMI) form, existence of a stabilizing observer gain matrix of UIO will be assured by checking whether the quadratic stability margin of the error dynamics is greater than the Lipschitz constant or not. If quadratic stability margin is less than a Lipschitz constant, the coordinate transformation may be used to reduce the Lipschitz constant in the new coordinates. Furthermore, to reduce the maximum singular value of the observer gain matrix elements, an object function to minimize it will be optimally designed by modifying its magnitude so that amplification of sensor measurement noise is minimized via multi-objective optimization algorithm. The performance of UIO is compared to a nonlinear observer (Luenberger-like) with an application to a flexible joint robot system considering a change of load and disturbance. Finally, it is validated via simulations that the estimated angular position and velocity provide true values even in the presence of unknown inputs.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.75-80
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• 2004

Vehicle structures are composed of many substructure connected to one another by various types of mechanical joints. In vehicle engineering it is important to study these connected structures under various dynamic forces for the evaluations of fatigue life and stress concentration exactly. It is difficult to obtain the accurate load history of specified positions because of the errors such as modeling, measurement and etc. In the beginning of design exact load data are actually necessary for the fatigue strength and life analysis to minimize the cost and time of designing. In this paper, the procedure of practical dynamic force determination is developed by the combination of the principal stresses of F. E. Analysis and experiment. Least square pseudo inverse matrix is adopted to obtain in inverse matrix of analyzed stresses matrix. The error minimization method utilizes the inaccurate measured error and the shifting error that the whole data is stiffed over real data. The least square criterion is adopted to avoid these non. Finally, to verify the proposed procedure, a bus is analyzed. This measurement and prediction technology can be extended to the structural modification of any geometric shape in complex structure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.11
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• pp.1621-1628
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• 2004

This paper proposes a design methodology for the robust observer using the eigenstructure assignment in multi-output systems so that the observer is less sensitive to the ill-conditioning factors such as unknown initial estimation error, modeling error and measurement bias in transient and steady-state observer performance. The robustness of the observer can be achieved by selecting the desired eigenvector matrix to have a small condition number that guarantees the small upper bound of the estimation error. So the left singular vectors of the unitary matrix spanned by space of the achievable eigenvectors are selected as a desired eigenvectors. Also, this paper proposes how to select the desired eigenvector based on the measure of observability and designs the observer with small gain. An example of a spindle drive system is simulated to validate the robustness to the ill-conditioning factors in the observer performance.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.39-44
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• 2003

It was shown that the robustness of deterministic observers with respect to modeling errors, measurement bias and round-off errors can be represented by a single performance index the condition number of the observer eigenvector matrix. In this paper, a robust observer for multi-output systems is designed using the left eigenstructure assignment, where the observer gain can not be determined uniquely with respect to the desired observer poles. Utilizing the eigenstructuer assignment for the robustness of the observer, the desired eigenvector matrix is selected to achieve the observer eigenvector matrix with the small condition number. The performance of the designed robust observer is evaluated in a spindle-drive simulation example where the load speed to be estimated based on the measured signals.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.406-410
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• 1991

This paper presents an improved algorithm of optimal measurement system design with a reliability evaluation method for large power system. The proposed algorithm is developed to consider the dummy bus and to achieve highest accuracy of the state estimator as well with the limited Investment cost. The dummy bus in the power system is impossible to install measurement meter, while real and reactive power measurement values are exactly zero. Thus, the effect on these dummy bus measurements is considered in the proposed algorithm. On the other hand, P/C model is developed by taking advantage of the matrix sparsity. The improved program is successfully tested for KEPCO system with PSS/E lineflow calculated data package.