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Neural network-based nonlinear dynamic inversion control of variable-span morphing aircraft

Jihoon Lee, Youdan Kim

Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, Vol. 234, No. 10, pp. 1624-1637, 2020 · 30 citations

Figure 1. F-18 HARV and assumed variable-span geometry.
Figure 1. F-18 HARV and assumed variable-span geometry.
Figure 2. Functional block diagram of the command augmentation system.
Figure 2. Functional block diagram of the command augmentation system.
Figure 7. Simulation result: push-over and pull-up.
Figure 7. Simulation result: push-over and pull-up.

Figures and captions reproduced from the paper (© the authors and original publisher).

A nonlinear command and stability augmentation system is designed based on feedback linearization for a morphing aircraft in the presence of different variable-span configurations. A variable-span morphing aircraft model is obtained by modifying a conventional aircraft model. Feed-forward neural networks are trained to learn the inverse dynamics in various morphing configurations and flight conditions. An attitude orientation system is designed to stabilize the airframe and track the commanded angular rates. Finally, an online adaptive mechanism is employed to compensate for inversion error. Even when the aircraft is changing the morphing configuration while maneuvering, the proposed design satisfies the desired handling quality specifications. Consequentially, the proposed design provides another degree of freedom to manipulate the morphing configuration, and therefore agility or fuel efficiency can be improved. Numerical simulation is performed to demonstrate the effectiveness of the proposed scheme.

SAGE Journalshttps://journals.sagepub.com/doi/10.1177/0954410019846713DOI: 10.1177/0954410019846713https://doi.org/10.1177/0954410019846713BibTeX@article{Lee2020, title = {Neural network-based nonlinear dynamic inversion control of variable-span morphing aircraft}, author = {Jihoon Lee and Youdan Kim}, year = {2020}, journal = {Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering}, volume = {234}, number = {10}, pages = {1624-1637}, doi = {10.1177/0954410019846713}, }

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