@inbook{3f141d06155744f6a01956817687d1b6,
title = "Design optimal experiments for parameter identification of a dynamic model with perturbed inputs",
abstract = "An optimization approach for sensor placement and input sequences to improve parameter identifiability in spatiotemporally dependent experiments, modelled by partial differential equations, is developed. Robust design criteria using bilevel optimization are applied in the approach. The determinant (D-optimality), the smallest eigenvalue (E-optimality) or the inverse of condition value (modified E-optimality) of the Fisher information matrix are applied as criteria. A greedy algorithm is used in the optimization procedure to avoid extremely long calculation time. The developed approach is illustrated towards the identification of kinetic parameters in a transient axial dispersion reactor model with perturbed inlets. Improvement of the parameter identifiability for the model is investigated fitting synthetic data generated by high-fidelity simulations with preset kinetic parameters. The performance of the three objective functions is also compared.",
author = "Ran Wang and Antonios Armaou and Robert Rioux",
note = "Publisher Copyright: {\textcopyright} 2024 Elsevier B.V.",
year = "2024",
month = jan,
doi = "10.1016/B978-0-443-28824-1.50581-0",
language = "English (US)",
series = "Computer Aided Chemical Engineering",
publisher = "Elsevier B.V.",
pages = "3481--3486",
booktitle = "Computer Aided Chemical Engineering",
}