• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.224-227
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• 1993

In this paper, a new LMS algorithm with a variable step size (VVS LMS) is presented. The change of step size .mu. at each iteration, which increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. The norm of the cross correlation between the estimation error and input signal is used. As a measure of the misadaptation degree. Simulation results are presented to compare the performance of the VSS LMS algorithm with the normalized LMS algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.318-323
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• 1993

The paper discusses the problem of computing coarser observation functions in supervisory control of discrete event systems. It is shown that when a supervisor that realizes a given language L has certain properties, L-realizability of a coarser observation function is equivalent to control-compatibility of the states in some subsets of the state space of the supervisor. This characterization is then used to devise an iterative procedure of computing coarser L-realizable observation functions, where supervisor reduction and L-realizability verification of an observation function are performed at each iteration.

• Journal of Industrial Technology
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• v.13
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• pp.33-41
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• 1993

In this paper, a new LMS algorithm with a fuzzy variable step size (FVS LMS) is presented. The change of step size ${\mu}$, at each iteration which is increases or decreases according to the misadaptation degree, is computed by a proportional fuzzy logic controller. As a result the algorithm has very good convergence speed and low steady-state misadjustment. As a measure of the misadaptation degree, the norm of the cross correlation between the estimation error and input signal is used. Simulation results are presented to compare the performance of the FVSS LMS algorithm with the normalized LMS algorithm.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 1999.02a
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• pp.85-88
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• 1999

The study of HTS bulk in permanent magnet applications requires the calculation of forces acting on the bulk. Currents distribution in HTS Superconducting bulk is very important to determine this forces. We have made computer program to find this current distribution and this program is applied to some simple disc-shape HTS bulk being magnetised in a uniform field. The techniques for determination of currents are FEM analysis and iteration method.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2001.02a
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• pp.61-64
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• 2001

Levitation force of a new magnetic levitation system using a super-conducting bulk magnet(SBM) and a permanent magnet(PM) was numerically calculated. The non-linear J-E relation of a SBM was modeled using a critical state model and iteration method, and demagnetization of a PM was considered using a demagnetization curve of a real PM. The maximum limitation of levitation force was found according to increasing the trapped field in a SBM. Finite element method was used for numerical calculation.

• Progress in Superconductivity and Cryogenics
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• v.1 no.2
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• pp.20-24
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• 1999

The study of HTS(High Temperature Superconducting) bulk in magnetic levitation system requires the calculation of currents distribution in HTS bulk is very important to determine this forces. We have made computer program to find this current distribution and levitation force. J-E relation in HTS bulk is extremely nonlinear, so iteration method must be used to determine the current distribution. We developed the method to determine the current distribution in the unifrom-field model and, using this method, calculated the levitation force in permanent-magnet-levitation model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.107-110
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• 1997

본 논문에서는 선형 이진 신경회로망 (Linear Binary Neural Network)을 최소화 하기 위하여, 입력패턴의 그룹화 가능성을 측정하는 조건함수를 제시한다. 또한 이 조건식으로 그룹화 우선순위를 정하고 iteration을 통해 신경회로망을 합성하는 MSP Term Grouping Algorithm을 보인다. 여려가지 예제에 대한 실제적 합성 실험을 통해 기존의 알고리즘과 제시된 알고리즘을 비교한 결과는 제시된 알고리즘이 기존의 알고리즘 보다 작은 크기의 선형 이진 신경회로망을 합성할 수 있는 향상된 방법임을 보여준다.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.176-179
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• 1989

Newton's OPF algorithm, for each iteration, solves with second order approximation of Lagraqngian function and sparse matrix technique. When load model is applied to this technique, load voltages have tendency to be fixed at lower limit. It makes the solution inadequte. In this paper, reference bus voltage specification technique suggested to make adequate load voltage. This method is verified useful 6-bus Ward-Hale sample system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.38.6-38
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• 2001

This paper presents a steady state optimal control algorithm for the weakly coupled discrete time bilinearsystems. The optimal solution for the overall system is obtained by solving a sequence of reduced order algebraic Riccati equations with an arbitrary accuracy. The obtained solutions converge to the optimal solutions by using the iteration method. We verify the proposed method by applying it to a real world numerical example.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1140-1145
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• 1989

A general dynamic iterative learning control scheme is proposed for a class of nonlinear systems. Relying on stabilizing high-gain feedback loop, it is possible to show the existence of Cauchy sequence of feedforward control input error with iteration numbers, which results in a uniform convergance of system state trajectory to the desired one.