Online state and unknown inputs estimation for nonlinear systems with particle filter based recursive expectation‐maximization algorithm

The article presents an innovative approach to simultaneously estimate states and unknown inputs (UIs) in nonlinear systems using a particle filter (PF) based recursive expectation‐maximization (EM) algorithm. This method is distinct from traditional iterative EM algorithms. During the E‐step, it ca...

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Vydané v:	International journal of robust and nonlinear control Ročník 34; číslo 13; s. 8768 - 8784
Hlavní autori:	Liu, Zhuangyu, Zhao, Shunyi, Wan, Haiying, Luan, Xiaoli, Liu, Fei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Bognor Regis Wiley Subscription Services, Inc 10.09.2024
Predmet:	Algorithms fermentation process Maximization Maximum likelihood estimates Nonlinear systems Optimization particle filter (PF) recursive EM algorithm Recursive functions unknown inputs (UIs)
ISSN:	1049-8923, 1099-1239
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