SYSID: An open-source library for system identification

Through this paper we introduce an exclusive library sysid for system identification in the R® platform. This open-source library, the first of its kind on this platform, is designed primarily for classroom training and academic purposes. The library contains routines for input design, simulation an...

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Bibliographic Details
Published in2017 Indian Control Conference (ICC) pp. 53 - 58
Main Authors Yerramilli, Suraj, Moudgalya, Kannan M., Tangirala, Arun K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2017
Subjects
Data models
Estimation
Libraries
Mathematical model
Parametric statistics
Predictive models
Training
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DOI10.1109/INDIANCC.2017.7846451

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Summary:Through this paper we introduce an exclusive library sysid for system identification in the R® platform. This open-source library, the first of its kind on this platform, is designed primarily for classroom training and academic purposes. The library contains routines for input design, simulation and standard estimation methods for understanding the subject of and developing data-driven models for linear-time invariant (LTI) systems. In the present version of the library, the class of models are restricted to non-parametric (impulse, step and frequency-response descriptions) and parametric input-output LTI models (the prediction-error family), while the methods include both the prediction-error minimization and the instrument-variable approaches. Methods for recursive estimation are also included. We demonstrate the various functionalities on two simulation case-studies.
DOI:10.1109/INDIANCC.2017.7846451