• 전기학회논문지
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• 제60권6호
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• pp.1229-1238
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• 2011

This paper deals with the lateral dynamic model of an all-wheel steered articulated vehicle to design a guidance controller. Nonlinear dynamic model of articulated vehicle is developed by complementing the model about the BRT system of California PATH in U. S. A. and the Phileas system of the APTS in Netherlands. Linear lateral dynamic model has been derived from the nonlinear dynamic model under some assumptions associated with the driving conditions. To design a guidance controller, we derive a transfer function that is steering angle as input and lateral acceleration as output from the linear lateral dynamic model by applying the parameter of vehicle that is developed by Korea Railroad Research Institute. To validate the dynamic model, nonlinear dynamic model has been compared with a vehicle model that has been programmed in ADAMS, and linear dynamic model has been compared with a nonlinear dynamic model under sime assumptions.

• Communications for Statistical Applications and Methods
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• 제29권6호
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• pp.695-708
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• 2022

Recently, several studies have been conducted using state space model. In this study, a dynamic linear model with state space model form is applied to stock data. The monthly returns for 135 Korean stocks are fitted to a dynamic linear model, to obtain an estimate of the time-varying 𝛽-coefficient time-series. The model formula used for the return is a capital asset pricing model formula explained in economics. In particular, the transition equation of the state space model form is appropriately modified to satisfy the assumptions of the error term. k-shape clustering is performed to classify the 135 estimated 𝛽 time-series into several groups. As a result of the clustering, four clusters are obtained, each consisting of approximately 30 stocks. It is found that the distribution is different for each group, so that it is well grouped to have its own characteristics. In addition, a common pattern is observed for each group, which could be interpreted appropriately.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.71-79
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• 2021

This study investigates the capital structure policy among Indonesian public companies. Previous studies suggest that capital structure policy could follow either static or dynamic behavior. The sample data used in this study was companies in the manufacturing sector, divided into three sub-sectors: the basic and chemical industry, miscellaneous industry, and the consumer goods industry. This study uses panel data from 2010 to 2018, with the Generalized Least Square (GLS) method and compared whether the fixed effect model is better than the common effect model. The results show that the dynamic and non-linear model tests can explain the capital structure determinants than the static and linear models. The dynamic model shows that the capital structure of a certain year is influenced by the capital structure of the previous year. The findings indicate that the company performs some adjustments in its capital structure policy by referring to the previous debt ratio, which implies support to the trade-off theory (TOT). The study also shows that profitability, tangible assets, size, and age explain the variation of capital structure policy. The patterns on the dynamic and non-linear confirm that capital structure runs in a nonlinear pattern, based on the sector, company condition, and the dynamic environment.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.33.1-33
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• 2001

We address a novel approach to identify a nonlinear dynamic system for Wiener models, which are composed of a linear dynamic system part followed by a nonlinear static part. The aim of system identification here is to provide the optimal mathematical model of both the linear dynamic and the nonlinear static parts in some appropriate sense. Assuming the nonlinear static part is invertible, we approximate the inverse function by a piecewise linear function. We estimate the piecewise linear inverse function by using the evolutionary computation approach such as genetic algorithm (GA) and evolution strategies (ES), while we estimate the linear dynamic system part by the least squares method. The results of numerical simulation studies indicate the usefulness of proposed approach to the Wiener model identification.

• Journal of the Korean Statistical Society
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• 제9권1호
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• pp.39-60
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• 1980

In the last paper, we have discussed the cannonical representatin of a dynamic linear model, on which some aggregation schemes were devised. The relationships of those aggregation schemes with dynamic properties were investigated. This paper tries to analyse she control strategy for the aggregated linear dynamic model and to investigate the dynamic properties of disaggregative model controlled by aggregated model. For the logical consistency with the last paper, all the sections and all the equations are numbered in a sequence.

• 전자공학회논문지S
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• 제34S권1호
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• pp.54-64
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• 1997

In this paper, a method of dynamic modeling and a dynamic control of a mobile robot are presented to show the superiority of the dynamic control comparing to the PD control. This dynamic model is derived from the cartesian coordinates using lagrange equations. Based upon the derived dynamic model, we implemented the dynamic control of the mobile robot using the computed torque method. Time varying non-linear friction terms are not incroporated in this dynamic model. Instead, those are considered as disturbances. This uncertainty in dynamic model of mobile robot is compensated by the outer loop controller using PD algorithm. The validity of this model and the control algorithm are confirmed through the experiments, where the dynamic control algorithm demonstrated robust velocity tracking performance against the unmodeled non-linear frictions. The superiority of this algorithm is demonstrated by comparing to classical PD control algorithm.

• 한국정밀공학회지
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• 제12권6호
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• pp.145-151
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• 1995

The first-order Taylor series expansion can be evaluated analytically from the formulated symbolic nonlinear dynamic equations. A closed-form linear dynamic euation is derived about a nominal trajectory. The state space representation of the linearized dynamics can be derived easily from the closed-form linear dynamic equations. But manual symbolic expansion of dynamic equations and linearization is tedious, time-consuming and error-prone. So it is desirable to manipulate the procedures using a computer. In this paper, the analytic linearization is performed using the symbolic language MATHEMATICA. Two examples are given to illustrate the approach anbd to compare nonlinear model with linear model.

• Journal of international Conference on Electrical Machines and Systems
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• 제3권4호
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• pp.394-397
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• 2014

This paper deals with the comparison and dynamic behavior of a moving-coil linear oscillatory actuator (MCLOA) with/without a mechanical spring. On the basis of a dynamic simulation model, the dynamic characteristics such as a current and a stroke of the MCLOA without the spring are predicted for various values of frequency. And then, dynamic test results are given to confirm the dynamic simulations. Finally, this paper describes the influence of the spring on the dynamic behavior of the MCLOA from the dynamic experiments of the MCLOA with/without the spring.

• Structural Engineering and Mechanics
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• 제56권1호
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• pp.27-47
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• 2015

In this study, the accuracy and reliability of fully nonlinear method against equivalent linear method for dynamic analysis of soil-structure interaction is investigated comparing the predicted results of both numerical procedures with the results of experimental shaking table tests. An enhanced numerical soil-structure model has been developed which treats the behaviour of the soil and the structure with equal rigour. The soil-structural model comprises a 15 storey structural model resting on a soft soil inside a laminar soil container. The structural model was analysed under three different conditions: (i) fixed base model performing conventional time history dynamic analysis, (ii) flexible base model (considering full soil-structure interaction) conducting equivalent linear dynamic analysis, and (iii) flexible base model performing fully nonlinear dynamic analysis. The results of the above mentioned three cases in terms of lateral storey deflections and inter-storey drifts are determined and compared with the experimental results of shaking table tests. Comparing the experimental results with the numerical analysis predictions, it is noted that equivalent linear method of dynamic analysis underestimates the inelastic seismic response of mid-rise moment resisting building frames resting on soft soils in comparison to the fully nonlinear dynamic analysis method. Thus, inelastic design procedure, using equivalent linear method, cannot adequately guarantee the structural safety for mid-rise building frames resting on soft soils. However, results obtained from the fully nonlinear method of analysis fit the experimental results reasonably well. Therefore, this method is recommended to be used by practicing engineers.