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Comparative study of co-design strategies for mission-specific design of quadcopters using differential flatness and Bayesian optimization

Jolan Wauters (UGent) , Tom Lefebvre (UGent) and Guillaume Crevecoeur (UGent)
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Abstract
Up until recently a sequential approach has been pursued for model-based design of dynamic mechatronic systems, where first the system is optimized for static performance measures after which its functionality is enhanced by optimizing its control trajectory. However, this impedes finding systems with concurrent optimal design and trajectory. Therefore multidisciplinary integrated design methods – co-design – have appeared that treat design and trajectory optimization at the same time. In this paper we examine two strategies for co-design, namely the simultaneous approach and the nested approach, for the optimal design of a quadcopter to perform a predefined task. To enable the former, Bayesian optimization is introduced in the nested framework to account for the computational cost. In regards to the latter, we rely on a flatness-based description of the dynamics of the aerial vehicle. Comparison of the two approaches with a sequential approach shows the added value of co-design to the design phase of dynamical systems and the impact of objective and constraint function formulation.
Keywords
Bayesian Optimization, Trajectory Optimization, Co-design, Unmanned Aerial Vehicles, Quadcopter, Flatness

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MLA
Wauters, Jolan, et al. “Comparative Study of Co-Design Strategies for Mission-Specific Design of Quadcopters Using Differential Flatness and Bayesian Optimization.” 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), IEEE, 2022, pp. 703–09, doi:10.1109/AIM52237.2022.9863284.
APA
Wauters, J., Lefebvre, T., & Crevecoeur, G. (2022). Comparative study of co-design strategies for mission-specific design of quadcopters using differential flatness and Bayesian optimization. 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 703–709. https://doi.org/10.1109/AIM52237.2022.9863284
Chicago author-date
Wauters, Jolan, Tom Lefebvre, and Guillaume Crevecoeur. 2022. “Comparative Study of Co-Design Strategies for Mission-Specific Design of Quadcopters Using Differential Flatness and Bayesian Optimization.” In 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 703–9. IEEE. https://doi.org/10.1109/AIM52237.2022.9863284.
Chicago author-date (all authors)
Wauters, Jolan, Tom Lefebvre, and Guillaume Crevecoeur. 2022. “Comparative Study of Co-Design Strategies for Mission-Specific Design of Quadcopters Using Differential Flatness and Bayesian Optimization.” In 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 703–709. IEEE. doi:10.1109/AIM52237.2022.9863284.
Vancouver
1.
Wauters J, Lefebvre T, Crevecoeur G. Comparative study of co-design strategies for mission-specific design of quadcopters using differential flatness and Bayesian optimization. In: 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). IEEE; 2022. p. 703–9.
IEEE
[1]
J. Wauters, T. Lefebvre, and G. Crevecoeur, “Comparative study of co-design strategies for mission-specific design of quadcopters using differential flatness and Bayesian optimization,” in 2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Sapporo, Japan (virtual), 2022, pp. 703–709.
@inproceedings{8764716,
  abstract     = {{Up until recently a sequential approach has been
pursued for model-based design of dynamic mechatronic systems,
where first the system is optimized for static performance
measures after which its functionality is enhanced by optimizing
its control trajectory. However, this impedes finding systems
with concurrent optimal design and trajectory. Therefore multidisciplinary integrated design methods – co-design – have appeared that treat design and trajectory optimization at the same
time. In this paper we examine two strategies for co-design,
namely the simultaneous approach and the nested approach,
for the optimal design of a quadcopter to perform a predefined
task. To enable the former, Bayesian optimization is introduced
in the nested framework to account for the computational cost.
In regards to the latter, we rely on a flatness-based description
of the dynamics of the aerial vehicle. Comparison of the two
approaches with a sequential approach shows the added value
of co-design to the design phase of dynamical systems and the
impact of objective and constraint function formulation.}},
  author       = {{Wauters, Jolan and Lefebvre, Tom and Crevecoeur, Guillaume}},
  booktitle    = {{2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)}},
  isbn         = {{9781665413084}},
  issn         = {{2159-6255}},
  keywords     = {{Bayesian Optimization,Trajectory Optimization,Co-design,Unmanned Aerial Vehicles,Quadcopter,Flatness}},
  language     = {{eng}},
  location     = {{Sapporo, Japan (virtual)}},
  pages        = {{703--709}},
  publisher    = {{IEEE}},
  title        = {{Comparative study of co-design strategies for mission-specific design of quadcopters using differential flatness and Bayesian optimization}},
  url          = {{http://doi.org/10.1109/AIM52237.2022.9863284}},
  year         = {{2022}},
}

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