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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
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Data-based controllability analysis of discrete-time linear time-delay systems
TL;DR: By using a data-based method, one can directly construct a controllability matrix using the measured state data without identifying system parameters, which can save time in practice and avoid corresponding identification errors.
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Least-squares estimation of input/output models for distributed linear systems in the presence of noise
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Identification of the nonlinear excitation force acting on a bowed string using the dynamical responses at remote locations
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A novel reduced order model for vortex induced vibrations of long flexible cylinders
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