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Applied system identification
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In this paper, the authors introduce the concept of Frequency Domain System ID (FDSI) and Frequency Response Functions (FRF) for time-domain models, as well as Frequency-Domain Models with Random Variables and Kalman Filter.Abstract:
1. Introduction. 2. Time-Domain Models. 3. Frequency-Domain Models. 4. Frequency Response Functions. 5. System Realization. 6. Observer Identification. 7. Frequency Domain System ID. 8. Observer/Controller ID. 9. Recursive Techniques. Appendix A: Fundamental Matrix Algebra. Appendix B: Random Variables and Kalman Filter. Appendix C: Data Acquisition.read more
Citations
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Journal ArticleDOI
Experimental Investigation of System-Identification-Based Damage Assessment on Structures
TL;DR: In this paper, the SI method identifies structural parameters by finite-element method by minimizing the error between measured and analytically computed responses, and a regularization scheme is applied to alleviate the ill-posedness of an inverse problem by adding a regularisation function to the primary error function.
Journal ArticleDOI
An approach to operational modal analysis using the expectation maximization algorithm
TL;DR: The results show that the application of the EM algorithm starting from the solution given by SSI is very useful to identify the vibration modes of a structure, discarding the spurious modes that appear in high order models and discovering other hidden modes.
Proceedings ArticleDOI
Bio-inspired flapping UAV design: a university perspective
TL;DR: Some key technical issues and the states-of-art of bio-inspired design of flapping UAVs are summarized with an introduction to authors' recent research results in this field.
Journal ArticleDOI
Efficient Reduced-Order System Identification for Linear Systems with Multiple Inputs
TL;DR: In this article, a single-composite-input method is proposed for large-scale linear dynamic systems with multiple inputs, which is based on a modification of the classical eigensystem realization algorithm and simultaneous injection of multiple inputs.
Book ChapterDOI
Modeling end-to-end packet delay dynamics of the internet using system identification
TL;DR: The ARX (Auto-Regressive eXogenous) model is used and its coefficients are determined using system identification and it is shown that the ARX model accurately captures the end-to-end packet delay dynamics if the orders of the ARZ model are appropriately chosen.