Combined estimation of the parameters and states for a multivariable state‐space system in presence of colored noise

2020 ◽  
Vol 34 (5) ◽  
pp. 590-613 ◽  
Author(s):  
Ting Cui ◽  
Feiyan Chen ◽  
Feng Ding ◽  
Jie Sheng

Algorithms ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 175
Author(s):  
Xuehai Wang ◽  
Feng Ding ◽  
Qingsheng Liu ◽  
Chuntao Jiang

This paper develops a bias compensation-based parameter and state estimation algorithm for the observability canonical state-space system corrupted by colored noise. The state-space system is transformed into a linear regressive model by eliminating the state variables. Based on the determination of the noise variance and noise model, a bias correction term is added into the least squares estimate, and the system parameters and states are computed interactively. The proposed algorithm can generate the unbiased parameter estimate. Two illustrative examples are given to show the effectiveness of the proposed algorithm.







2020 ◽  
Vol 142 ◽  
pp. 106579 ◽  
Author(s):  
Mladen Gibanica ◽  
Thomas J.S. Abrahamsson ◽  
Tomas McKelvey


2019 ◽  
Vol 67 (2) ◽  
pp. 794-813
Author(s):  
Minh Q. Phan ◽  
Dong-Huei Tseng ◽  
Richard W. Longman


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