• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.440-444
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• 1998

In this paper, we consider numerical solution of a H-J-B (Hamilton-Jacobi-Bellman) equation of elliptic type arising from the stochastic control problem. For the numerical solution of the equation, we take an approach involving contraction mapping and finite difference approximation. We choose the It(equation omitted) type stochastic differential equation as the dynamic system concerned. The numerical method of solution is validated computationally by using the constructed test case. Map of optimal controls is obtained through the numerical solution process of the equation. We also show how the method applies by taking a simple example of nonlinear spacecraft control.

• Earthquakes and Structures
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• v.14 no.5
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• pp.477-492
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• 2018

Recently, the adaptive nonlinear static analysis method has been widely used in the field of performance based earthquake engineering. However, the proposed methods are almost deterministic and cannot directly consider the seismic record uncertainties. In the current study an innovative Stochastic Adaptive Pushover Analysis, called "SAPA", based on equivalent hysteresis system responses is developed to consider the earthquake record to record uncertainties. The methodology offers a direct stochastic analysis which estimates the seismic demands of the structure in a probabilistic manner. In this procedure by using a stochastic linearization technique in each step, the equivalent hysteresis system is analyzed and the probabilistic characteristics of the result are obtained by which the lateral force pattern is extracted and the actual structure is pushed. To compare the results, three different types of analysis have been considered; conventional pushover methods, incremental dynamic analysis, IDA, and the SAPA method. The result shows an admirable accuracy in predicting the structure responses.

• Journal of KSNVE
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• v.8 no.4
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• pp.715-722
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• 1998

An investigation into the stochastic bifurcation and response statistics of an autoparameteric system under broad-band random excitation is made. The specific system examined is a spring-pendulum system with internal resonance, which is known to be a good model for a variety of engineering systems, including ship motions with nonlinear coupling between pitching and rolling motions. The Fokker-Planck equations is used to genrage a general first-order differential equation in the dynamic moment of response coordinates. By means of the Gaussian and non-Gaussian closure methods the dynamic moment equations for the random responses of the system are reduced to a system of autonomous ordinanary differential equations. In view of equilibrium solutions of this system and their stability we examine the stochastic bifurcation and response statistics. The analytical results are compared with results obtained by Monte Carlo simulation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.399-406
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• 1998

An investigation into the stochastic bifurcation and response statistits of an autoparameteric system under broad-band random excitation is made. The specific system examined is a spring-pendulum system with internal resonance, which is known to be a good model for a variety of engineering systems, including ship motions with nonlinear coupling between pitching and rolling motions. The Fokker-Planck equations is used to generate a general first-order differential equation in the dynamic moment of response coordinates. By means of the Gaussian and non-Gaussian closure methods the dynamic moment equations for the random responses of the system are reduced to a system of autonomous ordinary differential equations. In view of equilibrium solutions of this system and their stability we examine the stochastic bifurcation and response statistics. The analytical results are compared with results obtained by Monte Carlo simulation.

• Advances in aircraft and spacecraft science
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• v.3 no.4
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• pp.471-502
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• 2016

This paper presents the dynamic instability analysis of un-damped elastically supported piezoelectric functionally graded (FG) beams subjected to in-plane static and dynamic periodic thermomechanical loadings with uncertain system properties. The elastic foundation model is assumed as one parameter Pasternak foundation with Winkler cubic nonlinearity. The piezoelectric FG beam is subjected to non-uniform temperature distribution with temperature dependent material properties. The Young's modulus and Poison's ratio of ceramic, metal and piezoelectric, density of respective ceramic and metal, volume fraction exponent and foundation parameters are taken as uncertain system properties. The basic nonlinear formulation of the beam is based on higher order shear deformation theory (HSDT) with von-Karman strain kinematics. The governing deterministic static and dynamic random instability equation and regions is solved by Bolotin's approach with Newmark's time integration method combined with first order perturbation technique (FOPT). Typical numerical results in terms of the mean and standard deviation of dynamic instability analysis are presented to examine the effect of slenderness ratios, volume fraction exponents, foundation parameters, amplitude ratios, temperature increments and position of piezoelectric layers by changing the random system properties. The correctness of the present stochastic model is examined by comparing the results with direct Monte Caro simulation (MCS).

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.444-452
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• 2008

We propose an intelligent predictive control approach for a nonlinear networked control system (NCS) with time-varying delay and random observation. The control is given by the sum of a nominal control and a corrective control. The nominal control is determined analytically using a linearized system model with fixed time delay. The corrective control is generated online by a neural network optimizer. A Markov chain (MC) dynamic Bayesian network (DBN) predicts the dynamics of the stochastic system online to allow predictive control design. We apply our proposed method to a satellite attitude control system and evaluate its control performance through computer simulation.

• Journal of applied mathematics & informatics
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• v.35 no.3_4
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• pp.387-397
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• 2017

In order to react the dynamic behavior of the system more actually, it is necessary to solve the first problem of synchronization for Markovian jump complex network system in practical engineering problem. In this paper, the problem of local stochastic synchronization for Markovian nonlinear coupled neural network system is investigated, including nonlinear coupling terms and mode-dependent delays, that is less restriction to other system. By designing the Lyapunov-Krasovskii functional and applying less conservative inequality, we get a new criterion to ensure local synchronization in mean square for Markovian nonlinear coupled neural network system. The criterion introduced some free matrix variables, which are less conservative. The simulation confirmed the validity of the conclusion.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.281-290
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• 2004

A review of current procedures being used in engineering practice to analyze the response of structure/foundation systems subjected separately to different types of dynamic excitation, such as earthquake, sea-wave action, wind, or moving wheel loads, is presented. Separate formulations are given for analyzing systems in the time and frequency domains. Both deterministic and stochastic forms of excitation are treated. A distinction is made between demand and capacity analyses.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.1
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• pp.71-76
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• 2008

Nonlinear dynamic system under random excitation was analyzed by using stochastic method. A linearization method was used in order to linearize non-linear structural characteristics but the parametric excitation was used as it was given. An equivalent energy method which equalizes the expectation value of energy of the original nonlinear system and that of quasi-linearized system was proposed. Ito's differential rule was applied to obtain steady state moments. Quasi-linearization coefficients can be obtained the iterative calculation of linearization scheme and steady state moments. Monte Carlo simulation was used to verify the results of the proposed method. Nonlinear vibration of a slender beam was analyzed in this research. The analysis results were compared with Monte Carlo simulation result and showed good agreement. As the spectral density of the given excitation increased, the analysis results showed the better agreement with Monte Carlo simulation.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.91-99
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• 2010

In this study, the advanced numerical algorithm is developed which can performed the static and dynamic stochastic finite element analysis by considering the effect of uncertainties included in the member stiffness of steel cable-stayed bridges and seismic load. After conducting the linear and nonlinear initial shape analysis, the advanced numerical algorithm is the assessment tool which can performed structural the response analysis considering the static linearity and non-linearity of before or after induced intial tensile force, and examined the reliability assessment more efficiently. The verification of the developed numerical algorithm is evaluated by analyzing the regression analysis and coefficient of correlation using the direct monte carlo simulation. Also, the dynamic response characteristic and coefficient of variation of the steel cable-stayed bridge is calculated by considering the uncertainty of random variables using the developed numerical algorithm. In addition, the quantitative structural safety of the steel cable-stayed bridges is evaluated by conducting the reliability assessment based upon the dynamic stochastic finite element analysis result.