Multiple Bifurcations in a Polynomial Model of Bursting Oscillations

1998 ◽  
Vol 8 (3) ◽  
pp. 281-316 ◽  
Author(s):  
G. de Vries
2019 ◽  
Vol 41 ◽  
pp. 53-62
Author(s):  
I. A. Batyrev ◽  
◽  
S. M. Dobrovolskiy ◽  
A. M. Semenov ◽  
Yu. F. Strugov ◽  
...  

2021 ◽  
pp. 147592172199474
Author(s):  
Bin Xu ◽  
Ye Zhao ◽  
Baichuan Deng ◽  
Yibang Du ◽  
Chen Wang ◽  
...  

Identification of nonlinear restoring force and dynamic loadings provides critical information for post-event damage diagnosis of structures. Due to high complexity and individuality of structural nonlinearities, it is difficult to provide an exact parametric mathematical model in advance to describe the nonlinear behavior of a structural member or a substructure under strong dynamic loadings in practice. Moreover, external dynamic loading applied to an engineering structure is usually unknown and only acceleration responses at limited degrees of freedom of the structure are available for identification. In this study, a nonparametric nonlinear restoring force and excitation identification approach combining the Legendre polynomial model and extended Kalman filter with unknown input is proposed using limited acceleration measurements fused with limited displacement measurements. Then, the performance of the proposed approach is first illustrated via numerical simulation with multi-degree-of-freedom frame structures equipped with magnetorheological dampers mimicking nonlinearity under direct dynamic excitation or base excitation using noise-polluted measurements. Finally, a dynamic experimental study on a four-story steel frame model equipped with a magnetorheological damper is carried out and dynamic response measurement is employed to validate the effectiveness of the proposed method by comparing the identified dynamic responses, nonlinear restoring force, and excitation force with the test measurements. The convergence and the effect of initial estimation errors of structural parameters on the final identification results are investigated. The effect of data fusion on improving the identification accuracy is also investigated.


2014 ◽  
Vol 7 (5) ◽  
pp. 2477-2484 ◽  
Author(s):  
J. C. Kathilankal ◽  
T. L. O'Halloran ◽  
A. Schmidt ◽  
C. V. Hanson ◽  
B. E. Law

Abstract. A semi-parametric PAR diffuse radiation model was developed using commonly measured climatic variables from 108 site-years of data from 17 AmeriFlux sites. The model has a logistic form and improves upon previous efforts using a larger data set and physically viable climate variables as predictors, including relative humidity, clearness index, surface albedo and solar elevation angle. Model performance was evaluated by comparison with a simple cubic polynomial model developed for the PAR spectral range. The logistic model outperformed the polynomial model with an improved coefficient of determination and slope relative to measured data (logistic: R2 = 0.76; slope = 0.76; cubic: R2 = 0.73; slope = 0.72), making this the most robust PAR-partitioning model for the United States currently available.


2014 ◽  
Vol 687-691 ◽  
pp. 4060-4063
Author(s):  
Lu Sun ◽  
Long Long Xue ◽  
Jia Li Wang ◽  
Chun Yang Zhou

Memory effect of power amplifier (PA) due to broadband signals which adopt new modulation technique is becoming obvious, and worsening the linearity of PA. Behavioral modeling for RF (Radio Frequency) power amplifier is indispensable to design digital pre-distortion system by which we can promote the efficiency of PA. According to the simulation data in the software of ADS (Advanced Design System), behavioral models of MRF21085 amplifier can be established by MATLAB. Comparison of memory polynomial model and ADS simulation of MRF21085 amplifier demonstrate memory polynomial model can represent the electric characteristic of it exactly.


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