• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.44-52
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• 1994

In this paper, we assume that the dynamics of DC motor and nonlinear load are unknown. We propose an inverse dynamic model of DC motor and nonlinear load using the artificial neural network and construck speed control system based on the proposed dynamic model. We also propose another dynamic model with speed prediction scheme using the artificial neural network that removes the undesirable time delay effect caused by the computation time during the real-time control. We suggest a dynamic model which has arbitrary number of speed arguments and is especially effective when the motor and load has large moment of inertia. Next, we suggest a controller that combine the neurocontrol and PID control with constant gain. We show that the proposed neurocontrol systems have capabilities of noise rejection and generalization to have good velocity tracking through computer simulations and experiments.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.1-11
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• 2019

This study deals with a method based on the modified bivariate gamma function for reconstructions of dynamic behavior of delaminated composite plates subjected to impact loads. The proposed bivariate gamma function is associated with micro-genetic algorithms, which is capable of solving inverse problems to determine the stiffness reduction associated with delamination. From computing the unknown parameters, it is possible for the entire dynamic response data to develop a prediction model of the dynamic response through a regression analysis based on the measurement data. The validity of the proposed method was verified by comparing with results employing a higher-order finite element model. Parametric results revealed that the proposed method can reconstruct dynamic responses and the stiffness reduction of delaminated composite plates can be investigated for different measurements and loading locations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.147-154
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• 2019

The finite element model updating can be defined as the problem of finding the parameters of the finite element model which gives the closest response to the actual response of the structure by measurement. In the previous researches, optimization based methods have been developed to minimize the error of the response of the actual structure and the analytical model. In this study, we propose an inverse eigenvalue problem that can directly obtain the parameters of the finite element model from the target mode information. Deep Neural Networks are constructed to solve the inverse eigenvalue problem quickly and accurately. As an application example of the developed method, the dynamic finite element model update of a suspension bridge is presented in which the deep neural network simulating the inverse eigenvalue function is utilized. The analysis results show that the proposed method can find the finite element model parameters corresponding to the target modes with very high accuracy.

• Computational Structural Engineering : An International Journal
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• v.2 no.1
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• pp.33-42
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• 2002

A computationally efficient stiffness design method for building structures is proposed in which dynamic soil-structure interaction based on the wave-propagation theory is taken into account. A sway-rocking shear building model with appropriate ground impedances derived from the cone models due to Meek and Wolf (1994) is used as a simplified design model. Two representative models, i.e. a structure on a homogeneous half-space ground and a structure on a soil layer on rigid rock, are considered. Super-structure stiffness satisfying a desired stiffness performance condition are determined via an inverse problem formulation for a prescribed ground-surface response spectrum. It is shown through a simple yet reasonably accurate model that the ground conditions, e.g. homogeneous half-space or soil layer on rigid rock (frequency-dependence of impedance functions), ground properties (shear wave velocity), depth of surface ground, have extensive influence on the super-structure design.

• Management & Information Systems Review
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• v.38 no.1
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• pp.141-153
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• 2019

This study attempts to analyze the role of price discovery and the dynamic interdependence between KOSPI200 Index and KODEX Leverage(KODEX inverse), which are Korea's representative ETFs, using the vector error correction model. For the empirical analysis, one minute data of KODEX leverage, KODEX inverse and KOSPI200 index from April 10, 2018 to July 10, 2018 were used. The main results of the empirical analysis are as follows. First, between KODEX Leverage and KOSPI200 index, we found evidence that KODEX leverage plays a dominant role in price discovery. In addition, the KOSPI200 index is superior to price discovery between KODEX inverse and KOSPI200 index. Second, the KOSPI200 index has a relatively strong dependence on KODEX leverage, which is consistent with the KODEX leverage index playing a dominant role in price discovery compared to the KOSPI200 index. On the other hand, KOSPI200 index has a dependency on KODEX inverse index, but it is weaker than KODEX leverage index. These results are expected to be useful information for investors in capital markets.

• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.689-712
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• 2019

Time-series models like AR-ARX and ARMAX, provide a robust way to capture the dynamic properties of structures, and their residuals can be effectively used as features for damage detection. Even though several research papers discuss the implementation of AR-ARX and ARMAX models for damage diagnosis, they are basically been exploited so far for detecting the time instant of damage and also the spatial location of the damage. However, the inverse problem associated with damage quantification i.e. extent of damage using time series models is not been reported in the literature. In this paper, an approach to detect the extent of damage by combining the ARMAX model by formulating the inverse problem as a multi-constrained optimization problem and solving using a newly developed hybrid adaptive differential search with dynamic interaction is presented. The proposed variant of the differential search technique employs small multiple populations which perform the search independently and exchange the information with the dynamic neighborhood. The adaptive features and local search ability features are built into the algorithm in order to improve the convergence characteristics and also the overall performance of the technique. The multi-constrained optimization formulations of the inverse problem, associated with damage quantification using time series models, attempted here for the first time, can considerably improve the robustness of the search process. Numerical simulation studies have been carried out by considering three numerical examples to demonstrate the effectiveness of the proposed technique in robustly identifying the extent of the damage. Issues related to modeling errors and also measurement noise are also addressed in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2132-2137
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• 2005

This paper is concerned with computer simulations of a biped robot walking in dynamic gaits. To this end, a three-dimensional robot is considered possessing a torso and two identical legs of a kinematically ingenious design. Specific walking patterns are off-line generated meeting stability based on the ZMP condition. Subsequently, to verify whether the robot can walk as planned, a multi-body dynamics CAE code has been applied to the corresponding joint motions determined by inverse kinematics. In this manner, complex mass effects could be accurately evaluated for the robot model. As a result, key parameters to successful gaits are identified including inherent characteristics as well. Also, joint actuator capacities are found required to carry out those gaits.

• Journal of Power System Engineering
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• v.12 no.1
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• pp.72-79
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• 2008

This paper designs a looper-tension controller for mass-flow stabilization in hot strip finishing mills. By Newton's 2nd law and Hooke's law, nonlinear dynamic equations on the looper-tension system are firstly derived, and linearized by a linearization algorithm using a Taylor's series expansion. Moreover, a tension calculation model is obtained from the nonlinear dynamic equations which is called as a soft sensor of strip tension between two neighboring stands. Next, a looper-tension servo controller is designed by an ILQ(Inverse Linear Quadratic optimal control) algorithm, and it is combined with a minimal disturbance observer which to attenuate speed disturbances by AGC and operator interventions, etc.. Finally, it is shown from by a computer simulation that the proposed ILQ controller with a disturbance observer is very effective in stabilizing the strip mass-flow under some disturbances, moreover it has a good command following performance.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.980-984
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• 1990

In order to find the optimal control law for the precise trajectory tracking of a robot manipulator, a perturbational control method is proposed based on a linearized manipulator dynamic model which can be obtained in a very compact and computationally efficient manner using the dual number algebra. Manipulator control can be decomposed into two parts: the nominal control and the corrective perturbational control. The nominal control is precomputed from the inverse dynamic model using the quantities of a desired trajectory. The perturbational control is obtained by applying the second-variational method on the linearized dynamic model. Simulation results for a PUMA-560 robot show that, by using this controller, the desired trajectory tracking performance of the robot can be achieved, even in the presence of large initial positional disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.56.5-56
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• 2002

This paper studies on the feedback linearization of the looper system for hot strip mills, where the looper system plays an important role in regulating the strip tension. Firstly, nonlinear dynamic equations of the looper system are simply introduced. Secondly, using the static feedback linearization algorithm, a linear model of the looper system is obtained, of which usefulness is validated from comparison between the linear model and the nonlinear model, and design of LQI(Linear Ouadratic Integral optimal control) and ILQ (Inverse Linear Quadratic optimal control) looper control systems. In result, it is shown that the linear looper model by the feedback linearization well describes nonlin...