• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.153-163
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• 2009

Unlike the mean-variance approach, the stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum expected return by managing the constraint set and the objective function separately. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.792-804
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• 1990

This paper describes an efficient optimization algorithm by calculating sensitivity function for power system stabilization. In power system, the dynamic performance of exciter, governor etc. following a disturbance can be presented by a nonlinear differential equation. Since a nonlinear equation can be linearized for small disturbances, the state equation is expressed by a system matrix with system parameters. The objective function for power system operation will be related to the system parameter and the initial state at the optimal control condition for control or stabilization. The object function sensitivity to the system parameter can be considered to be effective in selecting the optimal parameter of the system.

• Korean Journal of Mathematics
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• v.26 no.1
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• pp.129-141
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• 2018

In this slush pile, we introduce a new kind of variational inclusions problem stated as random extended generalized nonlinear variational inclusions for random fuzzy mappings. We construct an iterative scheme for the this variational inclusion problem and also discuss the existence of random solutions for the problem. Further, we show that the approximate solutions achieved by the generated scheme converge to the required solution of the problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.7 no.1
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• pp.11-16
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• 1982

A method is described for the solution of a linearly constrained program with parametric nonlinear objective function. The algorithm proposed in this paper may be regarded as an extension of the simplex method for parametric linear programming. Namely, it specifies the basis at each stage such that feasibility ana optimality of the original problem are satisfied by the optimal solution of the reduced parametric problem involving only nonbasic variables. It is shown that under appropriate assumptions the algorithm is finite. Parametric procedures are also indicated for solving each reduced parametric problem by maintaining the Kuhn-Tucker conditions as the parameter value varies.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.156-161
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• 1994

In this paper, we consider an optimal control problem of a nonlinear stochastic system. Dynamic programming approach is employed for the formulation of a stochastic optimal control problem. As an optimality condition, dynamic programming equation so called the Bellman equation is obtained, which seldom yields an analytical solution, even very difficult to solve numerically. We obtain the numerical solution of the Bellman equation using an algorithm based on the finite difference approximation and the contraction mapping method. Optimal controls are constructed through the solution process of the Bellman equation. We also construct a test case in order to investigate the actual performance of the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.684-688
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• 1996

In this paper, to overcome drawbacks of variable structure control system a self-tuning fuzzy sliding mode control algorithm using gradient descent method is proposed. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties in the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to a one-degree of freedom robot arm. The results show that both alleviation of chattering and performance are achieved.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.870-875
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• 1987

The payload variation and modeling error can lye parameterized in such a way that known nonlinear functions are multiplied linearly by parameter errors. An adaptive control algorithm is derived for a perturbed linear system with such parameterization. Hence, in this approach no linear approximation of robot system is needed for the application of an adaptive law. The stability of the adaptive control algorithm is established and also supported by a computer simulation result.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.7-13
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• 1998

The gloval model is developed by combining this actuator formular with robot manipulator which is reported previously . The model initially represented in the form of coupled time-varying nonlinear dynamic system. It then decomposed into the decoupled linear model using nonlinear feedback and state transformation techniques. The new model employes the pole replacement method to improve the stability of the system. Using this new model, an robust control algorithm is developed. The proposed algorithm takes two state variables, position vector and velocity vector, and one input variable from actuator, input voltage.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1045-1048
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• 1999

In this paper, we report on a set of new algorithms to realize a nonlinear compressed-domain video/audio editor that overcomes various realization problems. For efficiency, the underlying algorithm, which uses a central data structure in the form of doubled linked lists, performs soft edits of cut and paste (which, in turn, involves soft implementations of frame type conversion) and addresses problems relating to video/audio synchronization and random access, and decoder buffer control.

• Journal of Power System Engineering
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• v.8 no.4
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• pp.24-30
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• 2004

In this study, a position synchronous control algorithm applied to two-axes pneumatic cylinder driving apparatus is proposed. The position synchronous control algorithm is composed of position controller and synchronous controller. The position controller is designed to minimize the effect of several nonlinear characteristics peculiar to the pneumatic cylinder driving apparatus on position control performance. The synchronous controller is designed to reduce the synchronous error. The effectiveness of the proposed controller is proved by simulation results.