• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.67-69
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• 2009

This paper deals with the consensus problem for multi-agent linear dynamic systems with parameter uncertainties. All the agents are identical high-order linear systems with parameter uncertainties and their state information is exchanged through a communication network. It is shown that a consensus is achieved if there exists a feasible solution to a set of linear matrix inequalities obtained for a simultaneous stabilization problem for multiple systems. A numerical example is presented to show the effectiveness of the proposed method.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.88-90
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• 2009

This paper deals with the consensus problem for multi-agent linear dynamic systems with communication delay. All the agents are identical high-order linear systems and their state information is exchanged through a communication network with constant communication delay. It is shown that a consensus is achieved if there exists a feasible solution to a set of linear matrix inequalities obtained for a simultaneous stabilization problem for multiple systems with delay. A numerical example is presented to show the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.5
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• pp.351-356
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• 2002

This papaer deals with a model reduction problem for linear systems with time varying parameters. For this problem, a controllability Grammian and an observability Grammian are introduced and computed by solving linear matrix inequalities. Using the controllability/observability Grammian, a balanced state space realization for linear parameter varying systems is obtained. From the balanced state space realization, a reduced model can be obtained by truncating not only states but also time varying parameters and an upper bound of the model reduction error is derived as well.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.29-36
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• 2004

This paper deals with a fractional model reduction for linear systems with time varying delayed states. A contractive coprime factorization of linear time delayed systems is defined and obtained by solving linear matrix inequalities. Using generalize controllability and observability gramians of tile contractive coprime factor, a balanced state space realization of the system is derived. The reduced model will be obtained by truncating states in the balanced realization and an upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is illustrated.

• Steel and Composite Structures
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• v.18 no.6
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• pp.1465-1478
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• 2015

The effect of cutting off fibers on transient load in a polymeric matrix composite lamina was studied in this paper. The behavior of fibers was considered to be linear elastic and the matrix behavior was considered to be linear viscoelastic. To model the viscoelastic behavior of matrix, a three parameter solid model was employed. To conduct this research, finite difference method was used. The governing equations were obtained using Shear-lag theory and were solved using boundary and initial conditions before and after the development of break. Using finite difference method, the governing integro-differential equations were developed and normal stress in the fibers is obtained. Particular attention is paid the dynamic overshoot resulting when the fibers are suddenly broken. Results show that considering viscoelastic properties of matrix causes a decrease in dynamic load concentration factor and an increase in static load concentration factor. Also with increases the number of broken fibers, trend of increasing load concentration factor decreases gradually. Furthermore, the overshoot of load in fibers adjacent to the break in a polymeric matrix with high transient time is lower than a matrix with lower transient time, but the load concentration factor in the matrix with high transient time is lower.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.1
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• pp.77-84
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• 2011

This study is to develop nonlinear analysis algorithm for transfer matrix method, which can be applied to continuous beam analysis. Gauss-Lobatto integral rule is adopted and the transfer matrix is derived from stiffness matrix. In the transfer matrix method, the system equation has a constant number of unknowns regardless of number of D.O.F. Therefore, the transfer matrix method has computational efficiencies not only in linear elastic analysis but also in nonlinear analysis. To verify the developed method, the analysis results of several examples are compared with commercial code in moment-curvature, moment-displacement and load-displacement relation.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1133-1143
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• 2009

In this work, we successfully extended dimensional differential transform method (DTM), by presenting and proving some new theorems, to solve the non-linear matrix differential Riccati equations(first and second kind of Riccati matrix differential equations). This technique provides a sequence of matrix functions which converges to the exact solution of the problem. Examples show that the method is effective.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.1-9
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• 2021

OpenGL compute shader is a shader stage that operate differently from other shader stage and it can be used for the calculating purpose of any data in parallel. This paper proposes a GPU-based parallel algorithm for computing sparse linear systems through conjugate gradient using an iterative method, which perform calculation on OpenGL compute shader. Basically, this sparse linear solver is used to solve large linear systems such as symmetric positive definite matrix. Four well-known matrix formats (Dense, COO, ELL and CSR) have been used for matrix storage. The performance comparison from our experimental tests using eight sparse matrices shows that GPU-based linear solving system much faster than CPU-based linear solving system with the best average computing time 0.64ms in GPU-based and 15.37ms in CPU-based.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.977-982
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• 2008

In this paper Haar functions are developed to approximate the solutions of continuous time linear system. Properties of Haar functions are first presented, and an explicit expression for the inverse of the Haar operational matrix is presented. Using the inverse of the Haar operational matrix the full order Stein equation should be solved in terms of the solutions of pure algebraic matrix equations, which reduces the computation time remarkably. Finally a numerical example is illustrated to demonstrate the validity of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.443-445
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• 1998

In this paper, an alternate method for state-covariance assignment for SISO(single input single output) linear systems is proposed. This method is based on the inverse solution of the Lyapunov matrix equation and the resulting formulas are similar in structure to the formulas for pole placement. Further, the set of all assignable covariance matrices to a SISO linear system is also characterized.