scholarly journals An investigation into accuracy, computation, and robustness of Stochastic Linearization of systems with saturation nonlinearities

Author(s):  
Sarnaduti Brahma ◽  
Timothy Foley ◽  
Sam Wisotzki ◽  
Hamid R. Ossareh
Author(s):  
Nguyen Cao Thang ◽  
Luu Xuan Hung

The paper presents a performance analysis of global-local mean square error criterion of stochastic linearization for some nonlinear oscillators. This criterion of stochastic linearization for nonlinear oscillators bases on dual conception to the local mean square error criterion (LOMSEC). The algorithm is generally built to multi degree of freedom (MDOF) nonlinear oscillators. Then, the performance analysis is carried out for two applications which comprise a rolling ship oscillation and two degree of freedom one. The improvement on accuracy of the proposed criterion has been shown in comparison with the conventional Gaussian equivalent linearization (GEL).


1993 ◽  
Vol 15 (4) ◽  
pp. 1-6
Author(s):  
Di Paola Mario ◽  
Nguyen Dong Anh

Stochastic linearization method is one of the most useful tools for analysis of nonlinear systems under random excitation. The fundamental idea of the classical stochastic linearization consists in replacing the original nonlinear equation by a linear one in such a way that the difference between two equations is minimized in the mean square value. In this paper a new version of the stochastic linearization is proposed. It is shown that for two nonlinear systems considered the new version gives good results for both the weak and strong nonlinearities.


2021 ◽  
Author(s):  
Sarnaduti Brahma ◽  
Mads R. Almassalkhi ◽  
Hamid R. Ossareh

2011 ◽  
pp. 20-65 ◽  
Author(s):  
ShiNung Ching ◽  
Yongsoon Eun ◽  
Cevat Gokcek ◽  
Pierre T. Kabamba ◽  
Semyon M. Meerkov

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