TY - GEN
T1 - Methods of system identification for monitoring slowly time-varying structural systems
AU - Johnson, E. A.
AU - Voulgaris, P. G.
AU - Bergman, L. A.
N1 - Publisher Copyright:
© 1997 IEEE.
PY - 1997
Y1 - 1997
N2 - It is often necessary to monitor the response of structural systems for reasons such as the prediction and avoidance of unstable behavior like flutter, monitoring structural parameters (e.g. natural frequency and damping, response of critical structural modes), and detection of structural damage or verification of structural integrity. Several different system identification methods are studied for the efficacy of their implementation for online monitoring of slowly time-varying structural systems. A few simple examples of such systems facilitate the evaluation of the performance, accuracy and ease of use of the various methods. Special attention is focused on exploring H ∞ -based identification methods and on a two-stage algorithm using a recursive least-squares identification. It is observed that H ∞ -based methods, while having advantages for many problems, especially in computing plant uncertainty bounds that are suitable for H ∞ control design, are not particularly well-suited for online structural monitoring. Recursive least-squares methods, however, are sufficiently computationally simple to provide real-time updates of structural parameters and, in conjunction with a Kalman filter, modal response with relatively good accuracy for systems with slowly varying characteristics.
AB - It is often necessary to monitor the response of structural systems for reasons such as the prediction and avoidance of unstable behavior like flutter, monitoring structural parameters (e.g. natural frequency and damping, response of critical structural modes), and detection of structural damage or verification of structural integrity. Several different system identification methods are studied for the efficacy of their implementation for online monitoring of slowly time-varying structural systems. A few simple examples of such systems facilitate the evaluation of the performance, accuracy and ease of use of the various methods. Special attention is focused on exploring H ∞ -based identification methods and on a two-stage algorithm using a recursive least-squares identification. It is observed that H ∞ -based methods, while having advantages for many problems, especially in computing plant uncertainty bounds that are suitable for H ∞ control design, are not particularly well-suited for online structural monitoring. Recursive least-squares methods, however, are sufficiently computationally simple to provide real-time updates of structural parameters and, in conjunction with a Kalman filter, modal response with relatively good accuracy for systems with slowly varying characteristics.
KW - H
KW - Kalman filters
KW - identification
KW - real-time monitoring
KW - recursive least squares identification
KW - structural system identification
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U2 - 10.1109/IIS.1997.645422
DO - 10.1109/IIS.1997.645422
M3 - Conference contribution
AN - SCOPUS:2142841457
T3 - Proceedings - Intelligent Information Systems, IIS 1997
SP - 569
EP - 573
BT - Proceedings - Intelligent Information Systems, IIS 1997
A2 - Adeli, Hojjat
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1997 International Conference on Intelligent Information Systems, IIS 1997
Y2 - 8 December 1997 through 10 December 1997
ER -