• 제목/요약/키워드: stochastic linearization

검색결과 43건 처리시간 0.022초

Direct implementation of stochastic linearization for SDOF systems with general hysteresis

  • Dobson, S.;Noori, M.;Hou, Z.;Dimentberg, M.
    • Structural Engineering and Mechanics
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    • 제6권5호
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    • pp.473-484
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    • 1998
  • The first and second moments of response variables for SDOF systems with hysteretic nonlinearity are obtained by a direct linearization procedure. This adaptation in the implementation of well-known statistical linearization methods, provides concise, model-independent linearization coefficients that are well-suited for numerical solution. The method may be applied to systems which incorporate any hysteresis model governed by a differential constitutive equation, and may be used for zero or non-zero mean random vibration. The implementation eliminates the effort of analytically deriving specific linearization coefficients for new hysteresis models. In doing so, the procedure of stochastic analysis is made independent from the task of physical modeling of hysteretic systems. In this study, systems with three different hysteresis models are analyzed under various zero and non-zero mean Gaussian White noise inputs. Results are shown to be in agreement with previous linearization studies and Monte Carlo Simulation.

통계적 부분선형화 방법을 이용한 선체의 불규칙 횡동요 운동의 해석 (Analysis of Random Ship Rolling Using Partial Stochastic Linearization)

  • 김동수;이원경
    • 대한조선학회논문집
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    • 제32권1호
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    • pp.37-41
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    • 1995
  • 불규칙 해상에서의 선체의 횡동요운동을 해석하기 위하여 통계적 부분선형화 방법을 사용하였다. 선형 1자유도계인 횡동요 운동 모델에 2차의 비선형 감쇠항과 3차 및 5차, 7차, 9차, 11차의 비선형 복원모멘트를 추가하였으며 불규칙 기진모멘트는 가우스 백색잡음으로 가정하였다. 이 해석 결과를 등가선형화 방법으로 구한결과와 비교한 결과 부분선형화 방법이 반드시 더 정확한 결과를 주는 것은 아니란 점을 확인하였다.

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최소위상 확률 비선형 시스템을 위한 필터링 조건과 신경회로망을 사용한 적응제어 (A FILTERING CONDITION AND STOCHASTIC ADAPTIVE CONTROL USING NEURAL NETWORK FOR MINIMUM-PHASE STOCHASTIC NONLINEAR SYSTEM)

  • 석진욱
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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    • pp.18-21
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    • 2001
  • In this paper, some geometric condition for a stochastic nonlinear system and an adaptive control method for minimum-phase stochastic nonlinear system using neural network me provided. The state feedback linearization is widely used technique for excluding nonlinear terms in nonlinear system. However, in the stochastic environment, even if the minimum phase linear system derived by the feedback linearization is not sufficient to be controlled robustly. In the viewpoint of that, it is necessary to make an additional condition for observation of nonlinear stochastic system, called perfect filtering condition. In addition, on the above stochastic nonlinear observation condition, I propose an adaptive control law using neural network. Computer simulation shoo's that the stochastic nonlinear system satisfying perfect filtering condition is controllable and the proposed neural adaptive controller is more efficient than the conventional adaptive controller.

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불규칙 교란을 받는 비행체에 장착된 비선형 시스템의 난진동 해석 (Analysis on random vibration of a non-linear system in flying vehicle due to stochastic disturbances)

  • 구제선
    • 대한기계학회논문집
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    • 제14권6호
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    • pp.1426-1435
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    • 1990
  • 본 연구에서는 확률론적 등가선형화 기법을 사용하여 비선형 랜덤 시스템을 선형화하였다.또 이 선형화된 시스템을 최근에 새로이 제안된 방법을 적용하여 비 백색잡음형태의 랜덤 가진을 받을 때 그 거동을 구하였다.

ADAPTIVE CONTROL USING NEURAL NETWORK FOR MINIMUM-PHASE STOCHASTIC NONLINEAR SYSTEM

  • Seok, Jinwuk
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.18-18
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    • 2000
  • In this paper, some geometric condition for a stochastic nonlinear system and an adaptive control method for minimum-phase stochastic nonlinear system using neural network are provided. The state feedback linearization is widely used technique for excluding nonlinear terms in nonlinear system. However, in the stochastic environment, even if the minimum phase linear system derived by the feedback linearization is not sufficient to be controlled robustly. the viewpoint of that, it is necessary to make an additional condition for observation of nonlinear stochastic system, called perfect filtering condition. In addition, on the above stochastic nonlinear observation condition, I propose an adaptive control law using neural network. Computer simulation shows that the stochastic nonlinear system satisfying perfect filtering condition is controllable and the proposed neural adaptive controller is more efficient than the conventional adaptive controller

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A stochastic adaptive pushover procedure for seismic assessment of buildings

  • Jafari, Mohammad;Soltani, Masoud
    • Earthquakes and Structures
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    • 제14권5호
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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.

Stochastic vibration response of a sandwich beam with nonlinear adjustable visco-elastomer core and supported mass

  • Ying, Z.G.;Ni, Y.Q.;Duan, Y.F.
    • Structural Engineering and Mechanics
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    • 제64권2호
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    • pp.259-270
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    • 2017
  • The stochastic vibration response of the sandwich beam with the nonlinear adjustable visco-elastomer core and supported mass under stochastic support motion excitations is studied. The nonlinear dynamic properties of the visco-elastomer core are considered. The nonlinear partial differential equations for the horizontal and vertical coupling motions of the sandwich beam are derived. An analytical solution method for the stochastic vibration response of the nonlinear sandwich beam is developed. The nonlinear partial differential equations are converted into the nonlinear ordinary differential equations representing the nonlinear stochastic multi-degree-of-freedom system by using the Galerkin method. The nonlinear stochastic system is converted further into the equivalent quasi-linear system by using the statistic linearization method. The frequency-response function, response spectral density and mean square response expressions of the nonlinear sandwich beam are obtained. Numerical results are given to illustrate new stochastic vibration response characteristics and response reduction capability of the sandwich beam with the nonlinear visco-elastomer core and supported mass under stochastic support motion excitations. The influences of geometric and physical parameters on the stochastic response of the nonlinear sandwich beam are discussed, and the numerical results of the nonlinear sandwich beam are compared with those of the sandwich beam with linear visco-elastomer core.

비선형 칼만 필터 기반의 지형참조항법 성능 비교 (A Performance Comparison of Nonlinear Kalman Filtering Based Terrain Referenced Navigation)

  • 목성훈;방효충;유명종
    • 한국항공우주학회지
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    • 제40권2호
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    • pp.108-117
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    • 2012
  • 본 논문은 비선형 필터 기법에 따른 지형참조항법 성능 분석에 관한 연구를 수행하였다. 지형참조항법에 사용되는 기본 필터에는 확장 칼만 필터(EKF)가 있다. 본 연구는 EKF 원형외에 반복형 EKF(IEKF), stochastic linearization(SL) 조건이 추가된 EKF-SL과 unscented Kalman Filter(UKF) 알고리듬을 소개한다. 또한, 연속적(sequential) 필터 외에 일괄적(batch)필터 기법인 칼만 필터 무리(bank of Kalman filters)를 이용한 항법 기술도 비교군으로 추가하고 필터 간 항법 성능을 분석한다. 가상 궤적을 가진 항공기 시뮬레이션을 통해 초기위치 오차가 클 때도 강건한(robust) 필터로 stochastic linearization EKF가 선정되었으며, 다만 빠른 항법 해의 수렴이 요구될 때에는 칼만 필터 무리를 이용한 일괄적 필터가 효과적인 것으로 분석되었다.

Investigation of effectiveness of double concave friction pendulum bearings

  • Ates, Sevket
    • Computers and Concrete
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    • 제9권3호
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    • pp.195-213
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    • 2012
  • This paper presents the investigation of the stochastic responses of seismically isolated bridges subjected to spatially varying earthquake ground motions including incoherence, wave-passage and site-response effects. The incoherence effect is examined by considering Harichandran and Vanmarcke coherency model. The effect of the wave-passage is dealt with various wave velocities in the response analysis. Homogeneous firm, medium and soft soil conditions are selected for considering the site-response effect where the bridge supports are constructed. The ground motion is described by filtered white noise and applied to each support points. For seismic isolation of the bridge, single and double concave friction pendulum bearings are used. Due to presence of friction on the concave surfaces of the isolation systems, the equation of motion of is non-linear. The non-linear equation of motion is solved by using equivalent linearization technique of non-linear stochastic analyses. Solutions obtained from the stochastic analyses of non-isolated and isolated bridges to spatially varying earthquake ground motions compared with each other for the special cases of the ground motion model. It is concluded that friction pendulum systems having single and double concave surfaces have important effects on the stochastic responses of bridges to spatially varying earthquake ground motions.

비선형시스템의 새로운 통계적 선형화방법 (A New Statistical Linearization Technique of Nonlinear System)

  • 이장규;이연석
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1990년도 하계학술대회 논문집
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    • pp.72-76
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    • 1990
  • A new statistical linearization technique for nonlinear system called covariance matching method is proposed in this paper. The covariance matching method makes the mean and variance of an approximated output be identical real functional output, and the distribution of the approximated output have identical shape with a given random input. Also, the covariance matching method can be easily implemented for statistical analysis of nonlinear systems with a combination of linear system covariance analysis.

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