DL-based Online Modeling of Nonlinear ODE-beam Cascaded Systems: Application to Flexible Morphing Aircraft
A deep learning (DL)-based online modeling scheme is proposed integrated deep auto-encoder and sparse identification of nonlinear dynamical systems for ordinary differential equation (ODE)-Euler-Bernoulli beam (EBB) cascaded systems. The online model dynamically evolves through new data streams and revising the reconstruction reduced-order dynamic system and reconstruction output for ODE-EBB cascaded systems. Simulation results on a flexible morphing aircraft are provided for validating the effectiveness of the DL-based online modeling approach and its superiority in modeling accuracy and efficiency is also validated by comparing with the DL-based offline one.
Authors
- Huai‐Ning Wu (ORCID: https://orcid.org/0000-0002-4366-5147)
- Jinfeng Zhang (ORCID: https://orcid.org/0000-0002-9065-626X)
- Jun‐Wei Wang (ORCID: https://orcid.org/0000-0003-0040-8914)
Institutions
- Zhejiang International Studies University (CN)
- Beihang University (CN)
- University of Science and Technology Beijing (CN)
Publication Details
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1109/icaisisas64483.2025.11052132
- Primary Topic
- Iterative Learning Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China