• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.5
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• pp.601-606
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• 1999

A Walsh function method is proposed in this report for the analysis and optimal control of linear time-delay systems, which is based on the Picard's iterative approximation and fast Walsh transformation. In this research, the following results are obtained: 1) The differential and integral equation can be solved by transforming into a simple algebraic equation as it was possible with the usual orthogonal function method: 2) General orthogonal function methods require usage of Walsh operational matrices for delay or advance and many calculations of inverse matrices, which are not necessary in this method. Thus, the control problems of linear time-delay systems can be solved much faster and readily.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.447-452
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• 2006

This paper presents a scheme to solve the congestion problem with phase-shifting transformer(PST) controls and power generation controls using linear programming method. A good design of PST and power generation control can improve total transfer capability(TTC) in interconnected systems. This paper deals with an application of optimization technique for TTC calculation. Linear programming method is used to maximize power flow of tie line subject to security constraints such as voltage magnitude and real power flow in interconnected systems. The results are compared with that of repeat power flow(RPF) and sequential quadratic programming(SQP). The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• Current Optics and Photonics
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• v.6 no.3
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• pp.304-312
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• 2022

Digital images of cultural relics captured using line scan cameras present limitations due to uneven intensity and low contrast. To address this issue, this report proposes a colour linear array image enhancement method that can maintain a constant colour. First, the colour linear array image is converted from the red-green-blue (RGB) colour space into the hue-saturation-intensity colour space, and the three components of hue, saturation, and intensity are separated. Subsequently, the hue and saturation components are held constant while the intensity component is processed using the established intensity compensation model to eliminate the uneven intensity of the image. On this basis, the contrast of the intensity component is enhanced using an improved local contrast enhancement method. Finally, the processed image is converted into the RGB colour space. The experimental results indicate that the proposed method can significantly improve the visual effect of colour linear array images. Moreover, the objective quality evaluation parameters are improved compared to those determined using existing methods.

• Smart Structures and Systems
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• v.30 no.1
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• pp.1-15
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• 2022

This article focuses on stability analysis and fuzzy controller synthesis for large neural network (NN) systems consisting of several interconnected subsystems represented by the NN model. Advanced and fuzzy NN differential inclusion (NNDI) for stability based on the developed algorithm with H infinity can be designed based on the evolved biological design. This representation is constructed using sector linearity for NN models. Sector linearity transforms a non-linear model into a linear model based on proposed operations. New sufficient conditions are realized in the form of LMI (linear matrix inequalities) to ensure the asymptotic stability of the trans-Lyapunov function. This transforms the nonlinear model into a linear model based on multiple rules. At last, a numerical case study with simulations is derived as illustration to prove its feasibility in real nonlinear structures.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.227-233
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• 1996

The Inverted Pendulum has been one of most popular nonlinear dynamic systems for the exploration of control techniques. This paper presents a new linear optimal control techniques and nonlinear neural network learning methods. The multiayered neural networks are used to add nonlinear effects on the linear optimal regulator(LQR). The new regulator can compensate nonlinear system uncertainties that are not considered in the LQR design, and can tolerated a wider range of uncertainties than the LQR alone. The new regulator has two neural networks for modeling and control. The neural network for modeling is used to obtain a more accurate model than the given mathematical equations. The neural network for control is used to overcome deficiencies by adding corrections to the linear coefficients of the LQR and by adding nonlinear effects on the LQR. Computer simulations are performed to show the applicability and a more robust regulator than the LQR alone.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.646-647
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• 2005

A recently published paper demonstrates the utility of allowing delays in state estimators for linear systems with unknown inputs. In this note, we point out an error in the derivation of the estimator.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.682-688
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• 2006

This paper deals with the delay-dependent and rate-independent stabilization of systems with multiple unknown time-varying delays and time-varying structured uncertainties. All the linear matrix inequalities based conditions are derived by employing free-weighting matrices to express the relationships between the terms in the Leibniz-Newton formula. The criteria do not require any tuning parameters. Numerical examples demonstrate the validity of the method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.6
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• pp.492-495
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• 2005

This paper deals with the problem of estimating the asymptotic stability region(ASR) of uncertain variable structure systems with bounded control. Using linear matrix inequalities(LMIs) we estimate the ASR and we show the exponential stability of the closed-loop control system in the estimated ASR. We show that our estimate is always better than the estimate of [3].

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.712-717
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• 2007

This paper is concerned with the problem of state feedback control of continuous-time nonlinear Markovian jump systems, which are represented by Takagi-Sugeno fuzzy models. A new method for designing state feedback stabilizing controllers is presented in terms of solvability of a set of linear matrix inequalities (LMIs), and it is shown that the new design method provides better or at least the same results of the existing method in the literature. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1823-1827
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• 1991

The problem regarding nonlinear systems has come to occupy an important position. In order to solve a nonlinear problem we have methods of linearization which are developed through linear approximation to adapt linear system theories. In this paper we present a formal linearization of nonlinear systems based on the discrete-Fourier transform (D.F.T.).