TY - GEN
T1 - Extension of a Fractional Model Identification Method for Fractional Dual-Pole Plus Dead-Time Models
AU - Gude, Juan J.
AU - Heppe, Gaizka
AU - Camacho, Oscar
AU - García Bringas, Pablo
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - This work introduces a novel technique for identifying fractional dual-pole plus dead-time models (FDPPDT) based on data derived from the reaction curve of the process. The proposed method effectively captures the fractional behavior of high-order systems with S-shaped step responses using a reduced-order model. Building upon the methodology outlined in previous work, this approach offers a straightforward and practical solution that is easy to apply and implement at the industrial level due to its proven effectiveness. The simplicity and effectiveness of the proposed technique are demonstrated through simulation examples, highlighting its advantages over other established methods. To the best of our knowledge, this is the first analytical technique presented to identify an FDPPDT model using the proposed approach.
AB - This work introduces a novel technique for identifying fractional dual-pole plus dead-time models (FDPPDT) based on data derived from the reaction curve of the process. The proposed method effectively captures the fractional behavior of high-order systems with S-shaped step responses using a reduced-order model. Building upon the methodology outlined in previous work, this approach offers a straightforward and practical solution that is easy to apply and implement at the industrial level due to its proven effectiveness. The simplicity and effectiveness of the proposed technique are demonstrated through simulation examples, highlighting its advantages over other established methods. To the best of our knowledge, this is the first analytical technique presented to identify an FDPPDT model using the proposed approach.
KW - Fractional-order systems
KW - Higher-order systems
KW - Identification method
KW - Process identification
KW - Reduced-order models
UR - https://www.scopus.com/pages/publications/105027191468
U2 - 10.1007/978-3-031-97950-7_12
DO - 10.1007/978-3-031-97950-7_12
M3 - Contribución a la conferencia
AN - SCOPUS:105027191468
SN - 9783031979491
T3 - Springer Proceedings in Mathematics and Statistics
SP - 183
EP - 212
BT - Mathematical Approaches to Challenges in Biology and Biomedicine - ICMASC 2024
A2 - Golubitsky, Martin
A2 - Boccaletti, Stefano
A2 - Pinto, Carla M.A.
PB - Springer
T2 - International Conference on Mathematical Analysis and Applications in Science and Engineering, ICMASC 2024
Y2 - 20 June 2024 through 22 June 2024
ER -