• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.156-161
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• 1994

In this paper, we consider an optimal control problem of a nonlinear stochastic system. Dynamic programming approach is employed for the formulation of a stochastic optimal control problem. As an optimality condition, dynamic programming equation so called the Bellman equation is obtained, which seldom yields an analytical solution, even very difficult to solve numerically. We obtain the numerical solution of the Bellman equation using an algorithm based on the finite difference approximation and the contraction mapping method. Optimal controls are constructed through the solution process of the Bellman equation. We also construct a test case in order to investigate the actual performance of the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.231-235
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• 1995

In this paper, the frozen time approach is used to analyze the nonlinear system with time varying parameter. Using the extended linearization, we propose two analytical methods that compute an upper bound of the Euclidean norm of the difference between state variable and equilibrium point of the given system. The propertise of the two methods are discussed with simple examples.

• Coupled systems mechanics
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• v.1 no.1
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• pp.39-57
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• 2012

This study intends to explore dynamic interaction behaviors between actively controlled maglev vehicle and guideway girders by considering the nonlinear forms of electromagnetic force and current exactly. For this, governing equations for the maglev vehicle with ten degrees of freedom are derived by considering the nonlinear equation of electromagnetic force, surface irregularity, and the deflection of the guideway girder. Next, equations of motion of the guideway girder, based on the mode superposition method, are obtained by applying the UTM-01 control algorithm for electromagnetic suspension to make the maglev vehicle system stable. Finally, the numerical studies under various conditions are carried out to investigate the dynamic characteristics of the maglev system based on consideration of the linear and nonlinear electromagnetic forces. From numerical simulation, it is observed that the dynamic responses between nonlinear and linear analysis make little difference in the stable region. But unstable responses in nonlinear analysis under poor conditions can sometimes be obtained because the nominal air-gap is too small to control the maglev vehicle stably. However, it is demonstrated that this unstable phenomenon can be removed by making the nominal air-gap related to electromagnetic force larger. Consequently it is judged that the nonlinear analysis method considering the nonlinear equations of electromagnetic force and current can provide more realistic solutions than the linear analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.526-531
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• 1997

To control nonlinear chemical processes, a new neural linearizing control scheme is proposed. This is a hybrid of a radial basis function(RBF) network and a linear controller, thus the control action applied to the process is the sum of both control actions. Firstly, to train the RBF newtork a linear reference model is determined by analyzing the past operating data of the process. Then, the training of the RBF newtork is iteratively performed to minimize the difference between outputs of the process and the linear reference model. As a result, the apparent dynamics of the process added by the RBF newtork becomes similar to that of the linear reference model. After training, the original nonlinear control problem changes to a linear one, and the closed-loop control performance is improved by using the optimum tuning parameters of the linear controller for the linear dynamics. The proposed control scheme performs control and training simultaneously, and shows a good control performance for nonlinear chemical processes.

• Structural Engineering and Mechanics
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• v.77 no.1
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• pp.19-35
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• 2021

Existing methods to estimate the probability of seismic pounding occurrence of adjacent buildings do not account for nonlinear behavior or only apply to simple lumped mass systems. The present study proposes an efficient method based on subset simulation for fragility and risk assessment of seismic pounding occurrence between nonlinear adjacent buildings neglecting pounding effects with application to finite element models. The proposed method is first applied to adjacent buildings modeled as elastoplastic systems with substantially different dynamic properties for different structural parameters. Seismic pounding fragility and risk of adjacent frame structures with different floor levels is then assessed, paying special attention to modeling the non-linear material behavior in finite element models. Difference in natural periods and impact location are identified to affect the pounding fragility simultaneously. The reliability levels of the minimum code-specified separation distances are also determined. In addition, the incremental dynamic analysis method is extended to assess seismic pounding fragility of the adjacent frame structures, resulting in higher fragility estimates for separation distances larger than the minimum code-specified ones in comparison with the proposed method.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.4
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• pp.169-178
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• 2020

In a previous paper, ambient vibration tests were conducted on a cable stayed bridge with resilient-friction base isolation systems (R-FBI) to extract the dynamic characteristics of the bridge and compare the results with a seismic analysis model. In this paper, a nonlinear seismic analysis model was established for analysis of the bridge to compare the difference in seismic responses between nonlinear time history analysis and multi-mode spectral analysis methods in the seismic design phase of cable supported bridges. Through these studies, it was confirmed that the seismic design procedures of the "Korean Highway Bridge Design Code (Limit State Design) for Cable Supported Bridges" is not suitable for cable supported bridges installed with R-FBI. Therefore, to reflect the actual dynamic characteristics of the R-FBI installed on cable-supported bridges, an improved seismic design procedure is proposed that applies the seismic analysis method differently depending on the seismic isolation effect of the R-FBI for each seismic performance level.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.3 s.43
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• pp.33-42
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• 2005

Frequency domain Volterra model is applied to nonlinear parameter identification procedure for dynamic systems modeled by nonlinear function. The frequency domain Volterra kernels, which correspond io linear, quadratic, and cubic transfer functions in lime domain, are incorporated in nonlinear parametric identification procedure. The nonlinear transfer functions, which can be derived from the Volterra series representation of the nonlinear differential equation of the system by Schetzen's method(1980), are directly used for modeling input output relation. The error is defined by the difference between the observed output and the estimated output which is calculated by substituting the observed input to nonlinear frequency domain model. The system parameters are searched by minimizing the error. Volterra model guarantees enough accuracy and convergence and the estimated coefficients have a good agreement with their actual values not only in the linear frequency region but also in the legion where the $2^{nd}\;or\;3^{rd}$ order nonlinearity is dominant.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2034-2036
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• 2002

In this paper, we propose the modeling of a chaotic nonlinear system using wavelet neural networks. In our modeling, we used the parameter adjusting method as the training method of a wavelet neural network. The difference between the actual output of a nonlinear chaotic system and that of a wavelet neural network adjusts the parameters of a wavelet neural network using the gradient-descent method. To verify the efficiency of this paper, we perform the simulation using Duffing system, which is a representative continuous time chaotic nonlinear system.

• Smart Structures and Systems
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• v.19 no.2
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• pp.213-224
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• 2017

The electromagnetic field can cause an essential change of the dynamic behavior of the railgun. The evaluation of the dynamics performance of railgun is a mandatory task. Here, a nonlinear electromagnetic force equation of the railgun is given in which the clearance, the thickness and the width of the rail are considered. Based on it, the nonlinear electromechanical coupled dynamics equations of Euler beam rails for the railgun are proposed. Using the equations, the nonlinear free vibration frequency of the railgun is investigated and the effects of the system parameters on the frequency are analyzed. The nonlinear forced responses of the rail to the electromagnetic excitation are investigated as well. The results show that as the nonlinearity of the railgun system is considered, the vibration frequencies of the railgun system increase; as the current in the rail increases, the difference between the natural frequencies and the nonlinear vibration frequencies increases significantly; the nonlinearity of the railgun system is more obvious for smaller distance between the two rails, smaller rail thickness, and smaller stiffness of the elastic foundation; the unstable dynamics state of the rail system occurs when the armature runs to the exit of the railgun. The results are useful for design and application of the railgun system.

• Journal of the Korean Applied Science and Technology
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• v.25 no.4
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• pp.438-445
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• 2008

For recipe prediction of colorant proportion showing nonlinear behavior, we modeled the effects of colorant proportion of basic colors on the target colors and predicted colorant proportion necessary for making target colors. First, colorant proportion of basic colors and color information indicated by the instrument was applied by a linear model and a multi-layer perceptrons model with back-propagation learning method. However, satisfactory results were not obtained because of nonlinear property of colors. Thus, in this study the neuro-fuzzy model with merit of artificial neural networks and fuzzy systems was presented. The proposed model was trained with test data and colorant proportion was predicted. The effectiveness of the proposed model was verified by evaluation of color difference(${\Delta}E$).