Parameter estimation of a three-axis spacecraft simulator using recursive least-squares approach with tracking differentiator and Extended Kalman Filter

2015 ◽  
Vol 117 ◽  
pp. 254-262 ◽  
Author(s):  
Zheyao Xu ◽  
Naiming Qi ◽  
Yukun Chen
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Least Squares ◽  
Extended Kalman Filter ◽  
Recursive Least Squares ◽  
Tracking Differentiator ◽  
Least Squares Approach

Enhanced Polynomial Chaos-Based Extended Kalman Filter Technique for Parameter Estimation

2017 ◽  
Vol 13 (2) ◽  
Author(s):  
Jeremy Kolansky ◽  
Corina Sandu
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Parameter Uncertainty ◽  
Polynomial Chaos ◽  
Recursive Least Squares ◽  
Mathematical Technique ◽  
Generalized Polynomial ◽  
State Tracking ◽  
Parameter Distributions

The generalized polynomial chaos (gPC) mathematical technique, when integrated with the extended Kalman filter (EKF) method, provides a parameter estimation and state tracking method. The truncation of the series expansions degrades the link between parameter convergence and parameter uncertainty which the filter uses to perform the estimations. An empirically derived correction for this problem is implemented, which maintains the original parameter distributions. A comparison is performed to illustrate the improvements of the proposed approach. The method is demonstrated for parameter estimation on a regression system, where it is compared to the recursive least squares (RLS) method.

scholarly journals Identification by Recursive Least Squares with Kalman Filter (RLS-KF) Applied to a Robotic Manipulator

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Darielson A. Souza ◽  
Josias G. Batista ◽  
Felipe J. S. Vasconcelos ◽  
Laurinda L. N. Dos Reis ◽  
Gabriel F. Machado ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Least Squares ◽  
Robotic Manipulator ◽  
Recursive Least Squares
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