Neural network-aided variational Bayesian adaptive cubature Kalman filtering for nonlinear state estimation

2017 ◽  
Vol 28 (10) ◽  
pp. 105003 ◽  
Author(s):  
Zhiyong Miao ◽  
Hongyang Shi ◽  
Yi Zhang ◽  
Fan Xu
Keyword(s):  
Neural Network ◽  
State Estimation ◽  
Kalman Filtering ◽  
Variational Bayesian ◽  
Nonlinear State Estimation ◽  
Nonlinear State

A Strong Tracking Cubature Kalman Filter for Nonlinear Estimation

2013 ◽  
Vol 313-314 ◽  
pp. 1115-1119
Author(s):  
Yong Qi Wang ◽  
Feng Yang ◽  
Yan Liang ◽  
Quan Pan
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Scaling Factor ◽  
Estimation Accuracy ◽  
Nonlinear State Estimation ◽  
Cubature Kalman Filter ◽  
Novel Method ◽  
Simulation Results ◽  
Tracking Filter ◽  
Nonlinear State

In this paper, a novel method based on cubature Kalman filter (CKF) and strong tracking filter (STF) has been proposed for nonlinear state estimation problem. The proposed method is named as strong tracking cubature Kalman filter (STCKF). In the STCKF, a scaling factor derived from STF is added and it can be tuned online to adjust the filtering gain accordingly. Simulation results indicate STCKF outperforms over EKF and CKF in state estimation accuracy.

Nonlinear state estimation of packed-bed tubular reactors

AIChE Journal ◽  
1979 ◽  
Vol 25 (4) ◽  
pp. 718-720 ◽  
Author(s):  
M. A. Soliman ◽  
W. Harmon Ray
Keyword(s):  
State Estimation ◽  
Packed Bed ◽  
Tubular Reactors ◽  
Nonlinear State Estimation ◽  
Nonlinear State
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