Open AccessSimultaneous identification of the all parameters for the Lorenz chaotic system
Author(s) -
Anton Guda,
Andrey Zimoglyad
Publication year - 2019
Publication title -
sistemnì tehnologìï
Language(s) - English
Resource type - Journals
eISSN - 2707-7977
pISSN - 1562-9945
DOI - 10.34185/1562-9945-6-125-2019-06
Subject(s) - lorenz system , chaotic , identification (biology) , computer science , representation (politics) , process (computing) , chaotic systems , control theory (sociology) , system identification , differential (mechanical device) , mathematics , algorithm , artificial intelligence , data mining , engineering , botany , control (management) , aerospace engineering , politics , political science , law , biology , measure (data warehouse) , operating system
Drawbacks of the adaptive-searching methods, related with the problem of multi-parameter dynamic system identification are explored and highlighted. New approach, based on “moving regression” method is proposed. New approach is a hybrid method; it combines features of the “moving average” method, linear regression method and differential system representation. This combination allows to simultaneously determining complex dynamic system parameters, in spite of its chaotic behavior and measurement errors. New method possibilities are explored via identification process numerical simulation for the Lorenz chaotic system.