Joint estimation of state, parameter, and unknown input for nonlinear systems: A composite estimation scheme

This study is concerned with the joint estimation problem for a class of nonlinear systems with the simultaneous unknown of the system state, the parameter, as well as the input signal. A composite estimation scheme is proposed where the estimator consists of both linear and nonlinear components, un...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:International journal of robust and nonlinear control Ročník 31; číslo 18; s. 9519 - 9537
Hlavní autoři: Wang, Licheng, Luo, Qi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bognor Regis Wiley Subscription Services, Inc 01.12.2021
Témata:
ISSN:1049-8923, 1099-1239
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This study is concerned with the joint estimation problem for a class of nonlinear systems with the simultaneous unknown of the system state, the parameter, as well as the input signal. A composite estimation scheme is proposed where the estimator consists of both linear and nonlinear components, under which the estimation performance is improved. The analysis and synthesis issues of the developed estimation algorithm are addressed for both the continuous‐time case and the discrete‐time case. By utilizing the Lyapunov stability theory combined with the singular value decomposition technique, sufficient conditions are established for both continuous‐time and discrete‐time cases to guarantee the convergence of the estimation error, rather than the boundedness in most of the existing literature. To facilitate the algorithm implementation in practical engineering, the Newton–Raphson method is adopted to deal with the feasibility issue for the discrete‐time case. Numerical simulations are provided for both the continuous‐ and discrete‐time cases to demonstrate the effectiveness of the proposed joint estimation strategies.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.5787