• 제어로봇시스템학회논문지
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• 제6권3호
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• pp.263-272
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• 2000

In this paper we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastcic approximation method it is regarded as a stochastic recursive filter algorithm. In addition we provide a filtering and control condition for a stochastic nonlinear system called the perfect filtering condition in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable and the proposed neural controller is more efficient than the conventional LQG controller and the canonical LQ-Neural controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.592-597
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• 2003

In this paper, some differential geometric conditions for the observer using a recurrent neural network are provided in terms of a stochastic nonlinear system control. In the stochastic nonlinear system, it is necessary to make an additional condition for observation of stochastic nonlinear system, called perfect filtering condition. In addition, we provide a observer using a recurrent neural network for the observation of a stochastic nonlinear system with the proposed observation conditions. Computer simulation shows that the control performance of the stochastic nonlinear system with a observer using a recurrent neural network satisfying the proposed conditions is more efficient than the conventional observer as Kalman filter

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 춘계학술대회논문집
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• pp.750-753
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• 2005

An equivalent linearization technique based on Rayleigh peak distribution for friction damper and brace system (FDBS) under stochastic excitation is proposed. For verification, shaking table test of a small scale 3-story building model with the FDBS is conducted for various slip moment levels. Using experimental result, equivalent linearization of the FDBS is conducted based on Rayleigh peak distribution, which is compared with measured peak distribution. For comparative study, model updating technique is applied based on identified modal properties. Finally, complex modal analysis and time history analysis for the obtained equivalent linear systems are conducted and compared with experimental result

• 한국공작기계학회논문집
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• 제17권1호
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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.

• 한국해양공학회지
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• 제1권1호
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• pp.57-64
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• 1987

Methods of nonlinear stochastic analysis of guyed towers are studied in this paper. Two different kinds of nonlinearities are considered. They are the nonlinear restoring force from the guying system and the nonlinear hydrodynamic force. Analyses are carried out mainly in the frequency domain using linearization techniques. Two methods for the linearization of the nonlinear stiffness are presented, in which the effects of the steady offset and the oscillating component of the structural motion can be adequately analyzed. those two methods are the equivalent linearization method and the average stiffness method. The linearization of the nonlinear drag force is also carried out considering the effect of steady current as well as oscillatory wave motions. Example analyses are performed for guyed tower in 300m water. Transfer functions and the expected maximum values of the deck displacement and the bending moment near the middle of the tower are calculated. Numerical results show that both of the frequency domain methods presented in this paper predict the responses of the sturcture very reasonably compared with those by the time integration method utilzing the random simulations wave particla motions.

• 제어로봇시스템학회논문지
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• 제12권2호
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• pp.93-100
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• 2006

In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2005년도 학술발표회 논문집
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• pp.437-444
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• 2005

An equivalent linearization technique based on Rayleigh peak distribution for friction damper and brace system (FDBS) under stochastic excitation is proposed. For verification, shaking table test of a small scale 3-story building model with the FDBS is conducted for various slip moment levels. Using experimental result, equivalent linearization of the FDBS is conducted based on Rayleigh peak distribution, which is compared with measured peak distribution. For comparative study, model updating technique is applied based on identified modal properties. Finally, complex modal analysis and time history analysis for the obtained equivalent linear systems are conducted and compared with experimental result.

• 대한전기학회논문지
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• 제39권7호
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• pp.729-739
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• 1990

This paper deals with the fault detection problem in uncertain linear/non-linear systems having both undermodelling and noise. A robust fault detection method is presented which accounts for the effects of noise, model mismatch and nonlinearities. The basic idea is to embed the unmodelled dynamics in a stochastic process and to use the nominal model with a predetermined fixed denominator. This allows the input /output relationship to be represented as a linear function of the system parameters and also facilitate the quatification of the effect of noise, model mismatch and linearization errors on parameter estimation by the Bayesian method. Comparisons are made via simulations with traditional fault detection methods which do not account for model mismatch or linearization errors. The new method suggested in this paper is shown to have a marked improvement over traditional methods on a number of simulations, which is a consequence of the fact that the new method explicitly for the effects of undermodelling and linearization errors.

• 한국지진공학회논문집
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• 제14권2호
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• pp.1-13
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• 2010

본 논문에서는 비선형 지진격리교량의 최적 설계 방법을 제시하였다. 최적설계를 위한 목적함수로는 교각과 지진격리장치의 파괴확률을 고려하였으며, 상충하는 두 목적함수를 동시에 최적화하는 다수의 해를 효율적으로 검색하고자 유전자 알고리즘에 기반한 다목적 최적화기법을 도입하였다. 또한, 최적화 과정에서 요구되는 다수의 비선형 시간이력해석을 수행하지 않고도 교량의 확률적 응답을 효율적으로 예측할 수 있는 추계학적 선형화 방법을 접목하였다. 제시하는 방법의 효율성을 검증하기 위한 수치 예로서 실제 교량인 남한강교를 고려하였고, 제안하는 방법과 기존 비선형 시간이력해석을 이용한 생애주기비용 기반 설계법을 각각 적용하여 내진성능을 비교하였다. 내진성능을 비교한 결과, 제시하는 방법이 기존의 비용에 기반한 최적설계보다 우수한 성능 및 경제성을 보임을 검증하였다. 또한, 다양한 지진하중에 대해서도 제안된 방법이 보다 개선된 성능을 보임을 확인하였다.

• 한국해양공학회지
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• 제5권2호
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• pp.191-191
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• 1991