• Journal of Mechanical Science and Technology
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• v.15 no.1
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• pp.125-138
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• 2001

An efficient correction storage scheme on a structured grid is applied to a sequence of approximate Jacobian systems arising at each time step from a linearization of the discrete nonlenear system of equations, obtained by the implicit time discretization of the conservation laws for unsteady fluid flows. The contribution of freezing the Jacobian matrix to computing costs is investigated within the correction storage scheme. The performance of the procedure is exhibited by measuring CPU time required to obtain a fully developed laminar vortex shedding flow past a circular cylinder, and is compared with that of a collective iterative method on a single grid. In addition, some computed results of the flow are presented in terms of some functionals along with measured data. The computational test shows that the computing costs may be saved in favor of the correction storage scheme with the frozen Jacobian matrix, to a great extent.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.34-41
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• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.112-119
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• 2003

Generally, PID controller is not suitable to control multi variable system because it is very difficult to tune the PID gains. However, this paper shows that it is not hard to tune the PID gains if we can find a Jacobian matrix of the system. The Jacobian matrix expresses the ratio of output variations according to input variations. It is possible to adjust the input values in order to reduce the output error using the Jacobian. When the colt function is composed of error related terms, the gradient approach can tune the PID gains to minimize the function. In simulation, a hydrofoil catamaran with two inputs and two outputs is applied as a multi variable system. We can easily get the multi variable PID controller by the proposed teaming method. When the controller is compared with LQR controller, the performance is as good as that of LQR controller with a modeling equation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.11
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• pp.1353-1360
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• 2012

The Jacobian and singularity analysis of parallel robots is necessary to analyze robot motion. The derivations of the Jacobian matrix and singularity configuration are complicated and have no geometrical earning in the velocity form of the Jacobian matrix. In this study, the screw theory is used to derive the Jacobian of parallel robots. The statics form of the Jacobian has a geometrical meaning. In addition, singularity analysis can be performed by using the geometrical values. Furthermore, this study shows that the screw theory is applicable to redundantly actuated robots as well as non-redundant robots.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.4
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• pp.337-344
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• 2014

While implicit integration methods such as Newton's method have excellent stability for the analysis of stiff and constrained mechanical systems, they have the drawback that the evaluation and LU-factorization of the system Jacobian matrix required at every time step are time-consuming. This paper proposes a Jacobian update-free Newton's method in order to overcome these defects. Because the motions of all bodies in a vehicle model are limited with respect to the chassis body, the equations are formulated with respect to the moving chassis-body reference frame instead of the fixed inertial reference frame. This makes the system Jacobian remain nearly constant, and thus allows the Newton's method to be free from the Jacobian update. Consequently, the proposed method significantly decreases the computational cost of the vehicle dynamic simulation. This paper provides detailed generalized formulation procedures for the equations of motion, constraint equations, and generalized forces of the proposed method.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.189-196
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• 1994

This paper describes a parallel computing algorithm in Gauss elimination of Jacobian matrix to large-scale power system. The structure of Jacobian matrix becomes different according to ordering method of buses. In sequential computation buses are ordered to minimize the number of fill-in in the triangulation of the Jacobian matrix. The proposed method develops the parallelism in the Gauss elimination by using ND(nested dissection) ordering. In this procedure the level structure of the power system network is transformed to be long and narrow by using end buses which results in balance of computing load among processes and maximization of parallel computation. Each processor uses the sequential computation method to preserve the sqarsity of matrix.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.163-166
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• 1993

This paper describes an parallell computing algorithm in Gauss elimination of Jacobian matrix to large-scale power system. The structure of Jacobian matrix becomes different according to ordering method of buses. In sequential computation buses are ordered to minimize the number of fill-in in the triangulation of the Jacobian matrix. The proposed method using ND(nested dissection) ordering develops the parallelism in the Gauss elimination to have balance of computing load among processes and each processor uses the sequential computation method to preserve the sparsity of matrix.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.311-315
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• 1998

Load Flow calculation methods can usually be divided into Gauss-Seidel method, Newton-Raphson method and decoupled method. Load flow calculation is a basic on-line or off-line process for power system planning, operation, control and state analysis. These days Newton-Raphson method is mainly used since it shows remarkable convergence characteristics. It, however, needs considerable calculation time in construction and calculation of inverse Jacobian matrix. In addition to that, Newton-Raphson method tends to fail to converge when system loading is heavy and system has a large R/X ratio. In this paper, matrix equation is used to make algebraic expression and then to solve load flow equation and to modify above defects. And it preserve certain part of Jacobian matrix to shorten the time of calculation. Application of mentioned algorithm to 14 bus, 39 bus, 118 bus systems led to identical result and the number of iteration got by Newton-Raphson method. The effect of time reduction showed about 28%, 30%, at each case of 39 bus, 118 bus system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1966-1973
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• 2001

The Jacobian matrix of the equations of motion of a system using velocity transformation technique is derived via variation methods to apply the implicit integration algorithm, DASSL. The concept of generalized coordinate partitioning is used to parameterize the constraint set with independent generalized coordinates. DASSL is applied to determine independent generalized coordinates and velocities. Dependent generalized coordinates, velocities, accelerations and Lagrange multipliers are explicitly retained in the formulation to satisfy all of the governing kinematic and dynamic equations. The derived Jacobian matrix of a system is proved to be valid and accurate both analytically and through solution of numerical examples.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1181-1188
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• 2017

This paper proposes the adoption of Monte Carlo perturbation theory to approximate the Jacobian matrix of coupled neutronics/thermal-hydraulics problems. The projected Jacobian is obtained from the eigenvalue decomposition of the fission matrix, and it is adopted to solve the coupled problem via the Newton method. This avoids numerical differentiations commonly adopted in Jacobian-free Newton-Krylov methods that tend to become expensive and inaccurate in the presence of Monte Carlo statistical errors in the residual. The proposed approach is presented and preliminarily demonstrated for a simple two-dimensional pressurized water reactor case study.