Advances in System Identification: Theory and Applications

Damien Gueho, Puneet Singla, Manoranjan Majji, Jer Nan Juang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper describes the main features and the most recent developments of system identification in the sense of data-driven modeling of dynamical systems. A brief summary of discrete time-invariant system identification techniques is provided, from the modern work of Gilbert, Kalman and Ho and the introduction of state-space realization, to the most recent developments of the identification of discrete time-varying and nonlinear systems. Important concepts of state-space realization, controllability and observability for linear systems are introduced along with more advanced methods to identify nonlinear dynamics. Numerical examples of varying complexity are considered to demonstrate the capability of the different approaches presented in this paper.

Original languageEnglish (US)
Title of host publication60th IEEE Conference on Decision and Control, CDC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages22-30
Number of pages9
ISBN (Electronic)9781665436595
DOIs
StatePublished - 2021
Event60th IEEE Conference on Decision and Control, CDC 2021 - Austin, United States
Duration: Dec 13 2021Dec 17 2021

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume2021-December
ISSN (Print)0743-1546
ISSN (Electronic)2576-2370

Conference

Conference60th IEEE Conference on Decision and Control, CDC 2021
Country/TerritoryUnited States
CityAustin
Period12/13/2112/17/21

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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