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Non‐parametric identification of a class of nonlinear multidegree dynamic systems
Author(s) -
Masri S. F.,
Bekey G. A.,
Sassi H.,
Caughey T. K.
Publication year - 1982
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.4290100102
Subject(s) - nonlinear system , parametric statistics , identification (biology) , system identification , frame (networking) , noise (video) , control theory (sociology) , sensitivity (control systems) , computer science , degrees of freedom (physics and chemistry) , parametric model , engineering , mathematics , electronic engineering , data modeling , artificial intelligence , telecommunications , statistics , botany , physics , control (management) , quantum mechanics , image (mathematics) , biology , database
A non‐parametric identification technique is presented for chain‐like multidegree‐of‐freedom non‐linear dynamic systems. The method uses information about the state variables of non‐linear systems to express the system characteristics in terms of two‐dimensional orthogonal functions. The technique is applied to a model of a steel frame that has been extensively investigated both analytically and experimentally. The method can be used with deterministic or random excitation to identify dynamic systems with arbitrary non‐linearities, including those with hysteretic characteristics. It is also shown that the method is easy to implement and needs much less computer time and storage requirements compared to the Wiener‐kernel approach. The method is shown to have low sensitivity to the effects of additive noise in the experimental data.