• Journal of Institute of Control, Robotics and Systems
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• v.7 no.7
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• pp.589-596
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• 2001

In this paper, a new design methodology for the optimal control of nonlinear systems described by the TS(Takagi-Sugeno) fuzzy model is proposed. First, a new theorem concerning the optimal stabilizing control of a general nonlinear dynamic system is proposed. Next, based on the proposed theorem and the inverse optimal approach, an optimal controller synthesis procedure for a TS fuzzy system is given, Also, it is shown that the optimal controller can be found by solving a linear matrix inequality problem. Finally, the proposed method is applied to the attitude control of a rigid spacecraft to demonstrate its validity.

• Advances in nano research
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• v.8 no.2
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• pp.149-156
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• 2020

The present paper explores forced vibrational properties of porosity-dependent functionally graded (FG) cylindrical nanoshells exposed to linear-type or triangular-type impulse load via classical shell theory (CST) and nonlocal strain gradient theory (NSGT). Employing such scale-dependent theory, two scale factors accounting for stiffness softening and hardening effects are incorporated in modeling of the nanoshell. Two sorts of porosity distributions called even and uneven have been taken into account. Governing equations obtained for porous nanoshell have been solved through inverse Laplace transforms technique to derive dynamical deflections. It is shown that transient responses of a nanoshell are affected by the form and position of impulse loading, amount of porosities, porosities dispensation, nonlocal and strain gradient factors.

• International Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.24-28
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• 2015

Composite materials are highly sensitive to the presence of manufacturing and service-related defects that can reach a critical size during service condition and thereby may affect the safety of the structure. When the structure undergoes some kind of damage, its stiffness reduces, in turn the dynamic responses change. In order to avoid safety issues early detection of damage is necessary. The knowledge of the vibration behavior of a structure is necessary and can be used to determine the existence as well as the location and the extent of damage.

• International Journal of Fluid Machinery and Systems
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• v.9 no.1
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• pp.75-84
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• 2016

Fluid-dynamic design of fluid machinery had heavily relied on empiricism and experimental observations for many years. Since 1980s, thanks to the advancements in Computational Fluid Dynamics (CFD), a variety of flow physics have been revealed. The contribution by CFD is indispensable; however, the challenge is required not only on the advancements in CFD technologies but also innovation of "design (optimization) technologies" because of the complex interactions between 3-D flow fields and the complex 3-D flow passage configurations, etc. This paper presents historical perspective on fluid machinery flow optimization in an industry with some messages for the future.

• 전기의세계
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• v.31 no.3
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• pp.204-208
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• 1982

The objective of this paper is to present a digital method for improving the lateral resolution of the B-scan images in the medical applications of ultrasound. The method is based upon a mathematical model of the lateral blurring caused by the finite beam width of the transducers. This model provides a simple method of applying a recursive scheme for image restoration with fast computation time. The point spread function (P.S.F.) can be measured by the reflective signals after scanning the small pins located along the depth of interest. From the measured P.S.F., one can compute the coefficient matrices of the inverse discrete-time dynamic state variable equation of the blurring process. Then, a recursive scheme for deblurring is applied to the recorded B-scan to improve the lateral resolution. One major advantage of the present recursive scheme over the transform method is in its applicability for the space-variant imaging, such as in the case of the rotational movement of transducer.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.221-223
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• 1993

The Hopfield model is defined as an adaptive dynamic system. In this paper we propose a modified neural network which is capable of solving linear programming problems and a set of linear equations. The model is directly implemented from the given system, and solves the problem without calculating the inverse of the matrices. We get the better stability results by the addition of scaling property and by using the nonlinearities in the linear programming neural networks.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.158-165
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• 1999

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses hybrid neuro-genetic technique. Feed-forward multilayer neural networks trained by back-propagation are used to learn the input)the location and dept of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this neural network and genetic algorithm, it is possible to formulate the inverse problem. Neural network training algorithm is the back propagation algorithm with the momentum method to attain stable convergence in the training process and with the adaptive learning rate method to speed up convergence. Finally, genetic algorithm is used to fine the minimum square error.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1760-1770
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• 2018

This paper presents a control bandwidth extension method for inverters with a low carrier ratio. The bandwidth is extended at the price of decreasing the phase margin. Then the phase margin is compensated by introducing an extra leading angle into an inverse Park transformation. The model of the controller with the proposed method is established. The magnitude and phase characteristics are also analyzed. Then the influence on system stability when the leading angle is introduced is analyzed. The proposed method is applied to design an inverter controller with both a large bandwidth and a desired phase margin, and the experimental results verify that the controller performs well in the steady-state and in terms of transient response.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.7
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• pp.610-614
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• 1991

This paper proposes a trajectory constrol fo a robot manipulator by using neural network. The inverse dynamic model of manipuator is learned by neural network. The manipulator is controlled by weight values of the learned neural network. The weight valuese is change with a torque of liner vontroller and a acceleration error. Phsically, the totlal torque for a manipualator is a sum of the liner controller torque and the nerural network controller torque. The proposed control effect is estimated by computer simulation.

• Structural Engineering and Mechanics
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• v.10 no.4
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• pp.359-369
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• 2000

Random loading identification has long been a difficult problem for Multi-Input-Multi-Output (MIMO) structure. In this paper, the Pseudo Excitation Method (PEM), which is an exact and efficient method for computing the structural random response, is extended inversely to identify the excitation power spectral densities (PSD). This identified method, named the Inverse Pseudo Excitation Method (IPEM), resembles the general dynamic loading identification in the frequency domain, and can be used to identify the definite or random excitations of complex structures in a similar way. Numerical simulations are used to reveal the the difficulties in such problems, and the results of some numerical analysis are discussed, which may be very useful in the setting up and processing of experimental data so as to obtain reasonable predictions of the input loading from the selected structural responses.