• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.4
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• pp.175-182
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• 2004

This paper presents a new method for finding the Block Pulse series coefficients, deriving the Block Pulse integration operational matrices and generalizing the integration operational matrices which are necessary for the control fields using the Block Pulse functions. In order to apply the Block Pulse function technique to the problems of state estimation or parameter identification more efficiently, it is necessary to find the more exact value of the Block Pulse series coefficients and integral operational matrices. This paper presents the method for improving the accuracy of the Block Pulse series coefficients and derives generalized integration operational matrix and applied the matrix to the analysis of linear time-invariant system.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.753-759
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• 1999

BPF(block pulse function) has been used widely in the system analysis and controller design. The integral operational matrix of BPF converts the system represented in the form of the differential equation into the algebraic problem. Therefore, it is important to reduce the error caused by the integral operational matrix. In this paper, a new integral operational matrix is derived from the approximating function using Lagrange's interpolation formula. Comparing the proposed integral operational matrix with another, the result by proposed matrix is closer to the real value than that by the conventional matrix. The usefulness of th proposed method is also verified by numerical examples.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.6
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• pp.351-358
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• 2003

This paper presents a new method for finding the Block Pulse series coefficients, deriving the Block Pulse integration operational matrices and generalizing the integration operational matrices which are necessary for the control fields using the Block Pulse functions. In order to apply the Block Pulse function technique to the problems of state estimation or parameter identification more efficiently, it is necessary to find the more exact value of the Block Pulse series coefficients and integral operational matrices. This paper presents the method for improving the accuracy of the Block Pulse series coefficients and derives the related integration operational matrices and generalized integration operational matrix by using the Lagrange second order interpolation polynomial.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2277-2279
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• 2003

This paper presents a new method for finding the Block Pulse series coefficients and deriving the Block Pulse integration operational matrices which are necessary for the control fields using the Block Pulse functions. This paper presents the method for improving the accuracy of the Block Pulse series coefficients and derives the related integration operational matrices by using the Lagrange second order interpolation polynomial and expands that matrix to general form.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.4
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• pp.198-204
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• 2003

In this paper, we presented a new algebraic iterative algorithm for the optimal control of the nonlinear systems. The algorithm is based on two steps. The first step transforms nonlinear optimal control problem into a sequence of linear optimal control problem using the quasilinearization method. In the second step, TPBCP(two point boundary condition problem) is solved by algebraic equations instead of differential equations using the new integral operational matrix of BPF(block pulse functions). The proposed algorithm is simple and efficient in computation for the optimal control of nonlinear systems and is less error value than that by the conventional matrix. In computer simulation, the algorithm was verified through the optimal control design of synchronous machine connected to an infinite bus.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.755-757
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• 1999

The operational properties of BPF(block-pulse functions) are much applied to the analysis of time-varying linear systems. The integral operational matrix of BPF converts the systems in the form of the differential equation into the algebraic problems. But the errors caused by using the integral operational matrix make it difficult that we exactly analyze time-varying linear systems. So, in this paper, to analyze time-varying linear systems we had used the recursive algorithm derived from the new integral operational matrix. And the usefulness of the proposed method is verified by the example.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2200-2202
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• 2003

In this paper, differentiation operational matrix for Haar function is derived. Proposed method only using a matrix calculation of Haar discrete matrix and block-pulse function's integration operational matrix. It would be possible to use to design an a1gebraic estimator for fault detection or unknown input observer effectively.

• Structural Engineering and Mechanics
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• v.67 no.4
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• pp.359-368
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• 2018

In this paper, a method is presented to identify the physical and modal parameters of multistory shear building based on substructural technique using block pulse generalized operational matrix and genetic algorithm. The substructure approach divides a complete structure into several substructures in order to significantly reduce the number of unknown parameters for each substructure so that identification processes can be independently conducted on each substructure. Block pulse functions are set of orthogonal functions that have been used in recent years as useful tools in signal characterization. Assuming that the input-outputs data of the system are known, their original BP coefficients can be calculated using numerical method. By using generalized BP operational matrices, substructural dynamic vibration equations can be converted into algebraic equations and based on BP coefficient for each story can be estimated. A cost function can be defined for each story based on original and estimated BP coefficients and physical parameters such as mass, stiffness and damping can be obtained by minimizing cost functions with genetic algorithm. Then, the modal parameters can be computed based on physical parameters. This method does not require that all floors are equipped with sensor simultaneously. To prove the validity, numerical simulation of a shear building excited by two different normally distributed random signals is presented. To evaluate the noise effect, measurement random white noise is added to the noise-free structural responses. The results reveal the proposed method can be beneficial in structural identification with less computational expenses and high accuracy.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2627-2629
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• 2000

This paper introduces the design of a reduced order observer with unknown inputs for the purpose of fault detection and isolation(FDI) in a class of bilinear systems. To Analyze the observer and FDI, this paper uses BPF(block-pulse functions). The operational properties of BPF are much applied to the analysis of bilinear systems. The integral operational matrix BPF converts the form of the differential equation into the algebraic problems.

• Honam Mathematical Journal
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• v.43 no.3
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• pp.373-383
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• 2021

In this study, a numerical method deals with the Chebyshev wavelet collocation and Adomian decomposition methods are proposed for solving Korteweg-de Vries equation. Integration of the Chebyshev wavelets operational matrices is derived. This problem is reduced to a system of non-linear algebraic equations by using their operational matrix. Thus, it becomes easier to solve KdV problem. The error estimation for the Chebyshev wavelet collocation method and ADM is investigated. The proposed method's validity and accuracy are demonstrated by numerical results. When the exact and approximate solutions are compared, for non-linear or linear partial differential equations, the Chebyshev wavelet collocation method is shown to be acceptable, efficient and accurate.