TY - GEN
T1 - Parameter Optimization and Model Validation of Quanser AERO using Modelica and RaPId
AU - Segerstrom, Eric
AU - Podlaski, Meaghan
AU - Khare, Abhijit
AU - Vanfretti, Luigi
N1 - KAUST Repository Item: Exported on 2022-06-21
Acknowledged KAUST grant number(s): OSR-2019-CoE-NEOM-4178.12
Acknowledgements: This work was supported in whole or in part by the National Aeronautics and Space Administration through the University Leadership Initiative Award Number 80NSSC19M0125 for the Center for High-Efficiency Electrical Technologies for Aircraft (CHEETA), and in part by the Center of Excellence for NEOM Research at the King Abdullah University of Science and Technology under grant OSR-2019-CoE-NEOM-4178.12. The second author is supported through the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE 1744655 and the Chateaubriand Fellowship of the Office for Science & Technology of the Embassy of France in the United States.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2021/7/28
Y1 - 2021/7/28
N2 - This paper presents an overview of the process for optimizing key electrical, mechanical, and aerodynamical parameters of a multi-domain model of the Quanser AERO, a reconfigurable, benchtop, twin-rotor system using RaPId, an open-source, modular toolbox for model validation and parameter estimation in MATLAB and Simulink. A particle swarm optimization algorithm and a constrained nonlinear optimization algorithm are compared for their efficacy in optimizing the afformentioned parameters of the AERO model in an effort to more accurately model the behavior of the device.
AB - This paper presents an overview of the process for optimizing key electrical, mechanical, and aerodynamical parameters of a multi-domain model of the Quanser AERO, a reconfigurable, benchtop, twin-rotor system using RaPId, an open-source, modular toolbox for model validation and parameter estimation in MATLAB and Simulink. A particle swarm optimization algorithm and a constrained nonlinear optimization algorithm are compared for their efficacy in optimizing the afformentioned parameters of the AERO model in an effort to more accurately model the behavior of the device.
UR - http://hdl.handle.net/10754/679217
UR - https://arc.aiaa.org/doi/10.2514/6.2021-3286
UR - http://www.scopus.com/inward/record.url?scp=85126794410&partnerID=8YFLogxK
U2 - 10.2514/6.2021-3286
DO - 10.2514/6.2021-3286
M3 - Conference contribution
SN - 9781624106118
BT - AIAA Propulsion and Energy 2021 Forum
PB - American Institute of Aeronautics and Astronautics
ER -