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The data filtering based multiple‐stage Levenberg–Marquardt algorithm for Hammerstein nonlinear systems
Author(s) -
Ji Yan,
Kang Zhen,
Liu Ximei
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5675
Subject(s) - levenberg–marquardt algorithm , nonlinear system , identification (biology) , algorithm , computer science , control theory (sociology) , artificial intelligence , artificial neural network , control (management) , quantum mechanics , biology , physics , botany
This article considers the parameter identification problem of multiple‐input single‐output Hammerstein nonlinear systems. Applying the data filtering technique, the input–output data are filtered. The filtered system is decomposed into multiple subsystems with fewer variables by using the hierarchical identification principle. The data filtering based multiple‐stage Levenberg–Marquardt algorithm is proposed for interactively identifying each subsystem. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed algorithms.