TY - GEN
T1 - Closed Loop System Identification Using Fractional Order Models
AU - Aboukheir, Hanna
AU - Di Teodoro, Antonio
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The growing digitalization of industrial processes under Industry 4.0 has encouraged the adoption of digital twins for process optimization; However, many of these processes are in closed loop and open loop identification techniques are not the most suitable for model estimation. In this work, it is proposed to use the Youla parametrization to transform the closed-loop identification problem into an open-loop one but using fractional models, starting from a known fractional controller to then experimentally estimate the process model, the proposal is evaluated through simulations in various closed loop systems.
AB - The growing digitalization of industrial processes under Industry 4.0 has encouraged the adoption of digital twins for process optimization; However, many of these processes are in closed loop and open loop identification techniques are not the most suitable for model estimation. In this work, it is proposed to use the Youla parametrization to transform the closed-loop identification problem into an open-loop one but using fractional models, starting from a known fractional controller to then experimentally estimate the process model, the proposal is evaluated through simulations in various closed loop systems.
KW - Closed loop identification
KW - Fractional order systems
KW - System Identification
UR - http://www.scopus.com/inward/record.url?scp=85218347487&partnerID=8YFLogxK
U2 - 10.1109/URUCON63440.2024.10850310
DO - 10.1109/URUCON63440.2024.10850310
M3 - Contribución a la conferencia
AN - SCOPUS:85218347487
T3 - 2024 IEEE URUCON, URUCON 2024
BT - 2024 IEEE URUCON, URUCON 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE URUCON, URUCON 2024
Y2 - 18 November 2024 through 20 November 2024
ER -