scholarly journals Monte Carlo Gaussian Sum Filter For State Estimation of Nonlinear Dynamical Systems∗∗The authors would like to thank Dept. of Science and Technology for partially funding this research under the grant 13DST057.

2016 ◽  
Vol 49 (1) ◽  
pp. 65-70
Author(s):  
Krishna Kumar Kottakki ◽  
Mani Bhushan ◽  
Sharad Bhartiya
Keyword(s):  
Monte Carlo ◽  
Dynamical Systems ◽  
State Estimation ◽  
Nonlinear Dynamical Systems ◽  
Science And Technology ◽  
Nonlinear Dynamical ◽  
Gaussian Sum

Journal Bearing Identification Under Operating Conditions

1984 ◽  
Vol 106 (2) ◽  
pp. 178-182 ◽  
Author(s):  
Roger Stanway
Keyword(s):  
Dynamical Systems ◽  
State Estimation ◽  
Numerical Experiments ◽  
Journal Bearing ◽  
Basic Problem ◽  
Nonlinear Dynamical Systems ◽  
Operating Conditions ◽  
Nonlinear Dynamical ◽  
Using Data ◽  
Bearing Dynamics

This note describes an approach to the problem of identifying linearized journal bearing dynamics using data acquired under normal operating conditions. The basic problem is reformulated so that an existing algorithm for state estimation in noisy nonlinear dynamical systems can be applied. The results of some numerical experiments are presented to demonstrate the feasibility of the approach.

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