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Non‐parametric identification of a class of non‐linear close‐coupled dynamic systems
Author(s) -
Udwadia F. E.,
Kuo ChinPo
Publication year - 1981
Publication title -
earthquake engineering and structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.218
H-Index - 127
eISSN - 1096-9845
pISSN - 0098-8847
DOI - 10.1002/eqe.4290090407
Subject(s) - identification (biology) , parametric statistics , class (philosophy) , system identification , series (stratigraphy) , noise (video) , computer science , parametric model , nonlinear system , algorithm , control theory (sociology) , engineering , mathematics , artificial intelligence , physics , data mining , paleontology , statistics , botany , control (management) , quantum mechanics , image (mathematics) , biology , measure (data warehouse)
A non‐parametric identification technique for the identification of arbitrary memoryless non‐linearities has been presented for a class of close‐coupled dynamic systems which are commonly met with in mechanical and structural engineering. The method is essentially a regression technique and expresses the non‐linearities as series expansions in terms of orthogonal functions. Whereas no limitation on the type of test signals is imposed, the method requires the monitoring of the response of each of the masses in the system. The computational efficiency of the method, its easy implementation on analogue and digital machines and its relative insensitivity to measurement noise make it an attractive approach to the non‐parametric identification problem.