scholarly journals Online Identification of a Two-Mass System in Frequency Domain using a Kalman Filter

2016 ◽  
Vol 37 (2) ◽  
pp. 133-147 ◽  
Author(s):  
Niko Nevaranta ◽  
Stijn Derammelaere ◽  
Jukka Parkkinen ◽  
Bram Vervisch ◽  
Tuomo Lindh ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Frequency Domain ◽  
Mass System ◽  
Online Identification

scholarly journals Lithium-Ion Battery SOC Estimation Based on Adaptive Forgetting Factor Least Squares Online Identification and Unscented Kalman Filter

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1733
Author(s):  
Hao Wang ◽  
Yanping Zheng ◽  
Yang Yu
Keyword(s):  
Kalman Filter ◽  
Least Squares ◽  
Unscented Kalman Filter ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Forgetting Factor ◽  
Soc Estimation ◽  
Online Identification ◽  
Adaptive Forgetting Factor ◽  
Adaptive Forgetting

In order to improve the estimation accuracy of the battery state of charge (SOC) based on the equivalent circuit model, a lithium-ion battery SOC estimation method based on adaptive forgetting factor least squares and unscented Kalman filtering is proposed. The Thevenin equivalent circuit model of the battery is established. Through the simulated annealing optimization algorithm, the forgetting factor is adaptively changed in real-time according to the model demand, and the SOC estimation is realized by combining the least-squares online identification of the adaptive forgetting factor and the unscented Kalman filter. The results show that the terminal voltage error identified by the adaptive forgetting factor least-squares online identification is extremely small; that is, the model parameter identification accuracy is high, and the joint algorithm with the unscented Kalman filter can also achieve a high-precision estimation of SOC.

scholarly journals Payload Mass Identification of a Single-Link Flexible Arm Moving under Gravity: An Algebraic Identification Approach

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Juan Carlos Cambera ◽  
Andres San-Millan ◽  
Vicente Feliu-Batlle
Keyword(s):  
Frequency Domain ◽  
Design Methodology ◽  
Vertical Plane ◽  
Sensor Noise ◽  
Online Identification ◽  
Flexible Arm ◽  
Single Link ◽  
Identification Approach ◽  
Payload Mass ◽  
Mass Identification

We deal with the online identification of the payload mass carried by a single-link flexible arm that moves on a vertical plane and therefore is affected by the gravity force. Specifically, we follow a frequency domain design methodology to develop an algebraic identifier. This identifier is capable of achieving robust and efficient mass estimates even in the presence of sensor noise. In order to highlight its performance, the proposed estimator is experimentally tested and compared with other classical methods in several situations that resemble the most typical operation of a manipulator.

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