• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.471-476
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• 1993

In this paper we proposed the digital implementation of an $H^{\infty}$-optimal controller using lifting technique and $H^{\infty}$-control theory. The discrete controller is obtained through iterative adjustment of sampling time and weighting function, which can ber performed by computing the L$_{2}$-induced input to output norm of the sampled-data system with bandlimited exogenous input. The resulting sampled-data bandlimited exogenous input. The resulting sampled-data system is stable and the performance including inter-sampling behaviour of the hybrid system can be also optimized.d.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.682-686
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• 1989

A new sufficient condition for the convergency of an iterative adaptive control algorithm is presented, in which a parameter estimator of the system together with an inverse system model to generate the control signal at each iteration. Also the result is extended to discrete time domain and a similar sufficient condition is derived.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.56-60
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• 1992

This paper addresses the problem of designing a neural network based controller for a discrete-time nonlinear dynamical system. Using two multi-layered neural networks we first design an indirect controller the weights of which are updated by the informations obtained from system identification. The weight update is executed by parameter optimization method under Lagrangian formulation. For the nonlinear dynamical system, we define several cost functions and by computer simulations analyze the control performances of them and the effects of penalty-weighting values.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.91-94
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• 1995

A newly developed discrete-time control design method for impact machines is proposed. It is composed of identification and control using neural networks, where the optimal controller with saturationn and no use of velocity measurements is obtained. By computer simulation, the proposed method is demonstrated to be effective: as the training progresses, the cost function becomes smaller, the proposed control is superior to PID control tuned with Ziegler-Nichols (Z-N) parameters; robust performance with respect to uncertainty, disturbances and working time is so good.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.1
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• pp.51-58
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• 1997

In this paper, we propose a stochastic LP model for determining an optimal input quantity in a single-product multi-stage production system with random yields. Due to the random yields in our model, each stage of the production system can result in defective items, which can be re-processed or scrapped at certain costs. We assume that the random yield at each stage follows an independent discrete empirical distribution. Compared to dynamic programming models that prevail in the literature, our model can easily handle problems of larger sizes.

• Journal of the Korean Mathematical Society
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• v.49 no.1
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• pp.99-112
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• 2012

This paper attempts to present a numerical method for solving optimal control problems. The method is based upon constructing the n-th degree Jacobi polynomials to approximate the control vector and use differentiation matrix to approximate derivative term in the state system. The system dynamics are then converted into system of algebraic equations and hence the optimal control problem is reduced to constrained optimization problem. Numerical examples illustrate the robustness, accuracy and efficiency of the proposed method.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.79-82
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• 2002

In this paper, we propose an adaptive repetitive control algorithm for the system the task of which is repetitive. The feedforward controller in the repetitive control system is modified by using the system parameter identifier in order to improve the convergence characteristics. The proposed algorithm is applied to the tracking control of a linear BLDC motor to which a periodic reference input is applied. It is illustrated by simulation results that the proposed adaptive repetitive control method yields better control performance than existing repetitive control even when modeling errors exist.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.326-329
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• 1995

PID control has been widely used for real control system Further, there are muchreasearches on control schemes of tuning PID gains. However, there is no results for discrete-time systems with unknown time-dealy and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown parameters and unknown tiem-delay system. A numerical simulation was presented to illuatrate the effectiveness of this method.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.737-739
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• 1998

This presentation describes an experiment to intergrated control, protection and measurement system configulation at KOWACO's Yongdam hydro-power station currently constructed by discrete electronic and electromechenical devices. The experiment is designed to exploit existing microcomputer technologies, digital signal processors, m/w&fiber optic communications. The theory of operation and advantages of the intergrated approach are discussed.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.172-177
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• 2007

Wavelet transforms provide basis functions for time-frequency analysis and have properties that are particularly useful for the compression of analogue point on wave transient and disturbance power system signals. This paper evaluates the compression properties of the discrete wavelet transform using actual power system data. The results presented in the paper indicate that reduction ratios up to 10:1 with acceptable distortion are achievable. The paper discusses the application of the reduction method for expedient fault analysis and protection assessment.