Parametric and nonparametric adaptive identification of nonlinear structural systems
| Autor: | Andrew W. Smyth, Anastassios G. Chassiakos, Elias B. Kosmatopoulos, Sami F. Masri |
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| Rok vydání: | 2000 |
| Předmět: |
Engineering
Mathematical optimization Adaptive control Artificial neural network Computer science business.industry Structural system Nonparametric statistics Control engineering Semiparametric model Adaptive identification Nonlinear system Identification (information) Applied mathematics Robust control business Parametric statistics |
| Zdroj: | Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334). |
| DOI: | 10.1109/acc.2000.876646 |
| Popis: | Adaptive estimation procedures have gained significant attention by the research community to perform real-time identification of nonlinear hysteretic structural systems under arbitrary dynamic excitations. The paper presents an overview of some of the authors' previous work in this area, and also discusses some of the new issues being tackled with regard to this class of problems. The trade-offs between parametric based modeling and nonparametric modeling of nonlinear hysteretic dynamic system behavior are discussed. A neural network based identification procedure is introduced. Both simulation and experimental results of the performance of the parametric and nonparametric methods are presented. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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