Parameter identification of time series models for linear dynamic structural systems using the least squares and total least squares criteria is investigated. Excitation and response time domain data are used to determine system parameters for autoregressive, moving average (ARMA) models. The method, or criteria, which is used to solve the set of overdetermined simultaneous equations developed from the time domain data affects the solution. A commonly used criteria, least squares, introduces the possibility of significant bias error in the system parameters and leads to bias errors in the modal parameter estimates. An alternative criteria, total least squares, provides an approach which appears to significantly reduce the bias error in the parameter estimates. These methods are applied to a simple, simulated system and then to flight flutter test data with particular emphasis on accurate modal damping estimates.
An investigation of the total least-squares criteria in time domain based, parameter identification for flight flutter testing
Untersuchung der Gesamtkriterien der kleinsten Quadrate in der bereichsbasierten Parameteridentifikation für Flugzeitflatterprüfungen
1995
11 Seiten, 10 Bilder, 5 Tabellen, 16 Quellen
Conference paper
English
Total Least-Squares Criteria in Parameter Identification for Flight Flutter Testing
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