• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1151-1154
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• 1993

The purpose of the paper is to explain some heuristic, common sense suppositions of fuzzy control. It is shown that Fuzzy Control is a kind of quasilinear interpolation of prototypes. Control function can be sufficiently exact represented as piecewise-linear function. The best interpolation is connected with normalized intersected fuzzy sets.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.5
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• pp.116-124
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• 2006

No matter how the equally spaced grounding grid is designed there are many problem. The best-fitted design for unequally spaced grounding grid is a part that must be considered. This paper Suggest a new way of calculation for grounding grid space of ground conductor by an algebraic function control(The first-order function, Root function, Polynomial function etc.) and on the optimal spaced grounding conductor that make the under 2[%] between maximum potential and minimum potential.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.15-20
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• 1995

Fuzzy membership functions are some kinds of mapping function for the fuzzification and the defuzzification. Triangle-shaped fuzzy membership functions are widely used in fuzzy controller, for it is easy to implement. In these membership functions, it is known that narrower fuzzy sets permit finer control near the operating point than that far from the operating point. $Supp{\acute{o}}se$ we have a membership function with narrower triangle near zero and wider triangle far from zero. The membership function will make fine control when small input is given and rough control at large input. Therefore the performance of the controller with that membership function will be enhanced. This paper presents how the width of triangle base in the fuzzy membership function has influence on the output using geometrical approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.339-344
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• 2000

This paper is concerned with the simplification of complex linear time-invariant systems. A simple technique is suggested using the well-known least squares method in the frequency domain. Given a high-order transfer function in the s- or z-domain, the squared-gain function corresponding to a low-order model is computed by the least squares method. Then, the low-order transfer function is obtained through the factorization. Three examples are given to illustrate the efficiency of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1014-1021
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• 2008

This paper proposes an intelligent sliding mode control method for robotic systems with the unknown bound of model uncertainties. In our control structure, the unknown bound of model uncertainties is used as the gain of the sliding controller. Then, we employ the function approximation technique to estimate the unknown nonlinear function including the width of boundary layer and the uncertainty bound of robotic systems. The adaptation laws for all parameters of the self-recurrent wavelet neural network and those for the reconstruction error compensator are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with model uncertainties and external disturbances. Accordingly, the proposed method can not only overcome the chattering phenomenon in the control effort but also have the robustness regardless of model uncertainties and external disturbances. Finally, simulation results for the five-link biped robot are included to illustrate the effectiveness of the proposed method.

• Proceedings of the KIPE Conference
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• 2011.11a
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• pp.315-316
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• 2011

This paper presents speed control scheme of the PMSM which has torque compensator to reduce the speed error and ripple. The proposed speed controller is based on the conventional PI control scheme. But the additional torque compensator which is different to the conventional differential controller produces a compensation torque to suppress speed ripple. In order to determine the proper compensation, the activation function which has discrete value is used in the proposed control scheme. With the proposed activation function, the compensation torque acts to suppress the speed error increasing. The proposed speed control scheme is verified by the computer simulation and experiments of 400[W] PMSM. In the simulation and experiments, the proposed control scheme has better control performance compare than the conventional PI and PID control schemes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.140-146
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• 2016

This paper proposes a control method of the Segway with unknown control coefficient and input saturation. To design a simple controller for the Segway with the model uncertainty, the prescribed performance function is used. Furthermore, an auxiliary variable is introduced to deal with unknown time-varying control coefficient and input saturation problem. Due to the auxiliary variable, function approximators are not used in this paper although all model uncertainties are unknown. Thus, the controller can be simple. From the Lyapunov stability theory, it is proved that all errors of the proposed control system remain within the prescribed performance bounds. Finally, the simulation results are presented to demonstrate the performance of the proposed scheme.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.129-138
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• 2015

This study describe a new method to control posture and velocity for a wheeled mobile robot using visual feedback control method with a position based visual feedback. To slove the problem of vibration phenomena which were shown in the previous researches using a simple switching function based on a threshold, the proposed visual servo control law introduces the fusion function based on a blending function. The chattering problem and rapid motion of the mobile robot can be eliminated. And we consider the nonlinearity of the wheeled mobile robot unlike the previous visual servo control laws using linear control methods to improve the performances of the visual servo control law. The proposed posture control law using visual servoing is verified by a theoretical analysis and simulation and experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.941-946
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• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• Journal of applied mathematics & informatics
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• v.18 no.1_2
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• pp.145-158
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• 2005

We formulate a stochastic control problem on proportional reinsurance that includes impulse and regular control strategies. For the first time we combine impulse control with regular control, and derive the expected total discount pay-out (return function) from present to bankruptcy. By relying on both stochastic calculus and the classical theory of impulse and regular controls, we state a set of sufficient conditions for its solution in terms of optimal return function. Moreover, we also derive its explicit form and corresponding impulse and regular control strategies.