@inproceedings{d5815a07d7f54c97ba64ce387d185aa0,
title = "Parameter identification from hybrid model using PSO and penalty functions",
abstract = "This work studies the parameter identification of a hybrid model with Particle Swarm Optimization. A hybrid model is based on selection functions that allow the switching between simple mathematical expressions in order to describe a complex behavior. In this work two performance functions are proposed to perform the identification: The former considers a switching between functions on their structure. The latter implements function penalty functions in order to avoid the evaluation of the selection functions. These functions test for the parameter identification of a Shape Memory Alloy model under a numerical simulation. The quality of the computed estimates is tested using statistical tools to assure repeatability and to verify the influence of the performance functions.",
keywords = "Hybrid model, Hysteresis, Parameter identification, Particle Swarm Optimization, Shape Memory Alloy, Smart actuator",
author = "Ricardo Cortez and Yair Lozano and Ruben Garrido",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2021 ; Conference date: 10-11-2021 Through 12-11-2021",
year = "2021",
doi = "10.1109/CCE53527.2021.9633108",
language = "Ingl{\'e}s",
series = "CCE 2021 - 2021 18th International Conference on Electrical Engineering, Computing Science and Automatic Control",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "CCE 2021 - 2021 18th International Conference on Electrical Engineering, Computing Science and Automatic Control",
address = "Estados Unidos",
}