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Applied system identification

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TLDR
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.

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Citations
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Operational Modal Analysis on an exhaust system

N. Moller, +1 more
TL;DR: In this paper, a modal analysis is made on the exhaust system of a passenger car and two scenarios were used: estimation using only the responses when excited by the engine during operation and classical input output modal analyses.

Optimal System Realization in Frequency Domain

TL;DR: Several approaches are presented to identify an experimental system model directly from frequency response data and an approach is introduced to fine-tune the model using non-linear programming methods to minimize the desired cost function.
Journal ArticleDOI

A Hybrid Parameter Estimation Algorithm for S-System Model of Gene Regulatory Networks

TL;DR: A hybrid algorithm is presented for identification and parameter estimation of gene network structure described by a S-system model that combines an optimization process with a system identification method commonly used in the aerospace community.
Journal ArticleDOI

Realization of State-Space Models for Wave Propagation Simulations

TL;DR: The superstable identification technique is reviewed and it is concluded that, using superstable-identified systems, the models are able to create reusable and reducible propagation-system models that accurately simulate the wave field using a fraction of the original computational resources.
Proceedings ArticleDOI

An experimental study on the closed-loop system identification by observer/controller identification (OCID) algorithm

TL;DR: In this article, the experimental results of the closed-loop system identification for a state-space model of an Inverted pendulum system using OCID in time domain are presented, with the assumption that existing feedback controller dynamics and open-loop systems model are unknown.