Real-time identification of ARX-SDP model using a rectangular moving window

Elvis Jara Alegria, Celso Pascoli Bottura

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

This paper proposes a real-time identification method for auto-regressive with exogenous inputs and state-dependent parameters (ARX-SDP). This model is always non-linear. We conveniently adapt Young's off-line approach to an real-time approach with reduced computational cost. Young's approach focuses on discovering state-parameter dependence. This implies to unveil the nonlinear structure of the system. The proposed real-time method focuses on monitoring the non-linear state-parameter dependence, detecting structural changes and updating the model structure in real time. Finally, applications to the real-time identification of state-dependent parameters are presented and structural changes are simulated in order to test our approach.

Idioma originalInglés
Título de la publicación alojadaICAC 2017 - 2017 23rd IEEE International Conference on Automation and Computing
Subtítulo de la publicación alojadaAddressing Global Challenges through Automation and Computing
EditoresJie Zhang
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9780701702618
DOI
EstadoPublicada - 23 oct. 2017
Publicado de forma externa
Evento23rd IEEE International Conference on Automation and Computing, ICAC 2017 - Huddersfield, Reino Unido
Duración: 7 set. 20178 set. 2017

Serie de la publicación

NombreICAC 2017 - 2017 23rd IEEE International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing

Conferencia

Conferencia23rd IEEE International Conference on Automation and Computing, ICAC 2017
País/TerritorioReino Unido
CiudadHuddersfield
Período7/09/178/09/17

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