Incremental Nonlinear Control Allocation for an Aircraft with Distributed Electric Propulsion

Conference Paper (2023)
Author(s)

P. de Heer (TU Delft - Team Mulders)

Coen de de Visser (TU Delft - Control & Simulation)

M.L. Hoogendoorn (Royal Netherlands Aerospace Centre NLR)

Henk W Jentink (Royal Netherlands Aerospace Centre NLR)

Research Group
Team Mulders
Copyright
© 2023 P. de Heer, C.C. de Visser, M.L. Hoogendoorn, Henk W Jentink
DOI related publication
https://doi.org/10.2514/6.2023-1248
More Info
expand_more
Publication Year
2023
Language
English
Copyright
© 2023 P. de Heer, C.C. de Visser, M.L. Hoogendoorn, Henk W Jentink
Research Group
Team Mulders
ISBN (print)
9781624106996
ISBN (electronic)
978-1-62410-699-6
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

In this paper, a new nonlinear control allocation method is presented for a distributed electric propulsion (DEP) aircraft. As the electric propellers can be used actively for control, in addition to the control surfaces, the DEP aircraft is over-actuated. This freedom in control effectors can be exploited with an appropriate control allocation method. All control effectors are, therefore, captured in the incremental nonlinear control allocation (INCA) method, which allows taking into account effector nonlinearities and interactions introduced by the propellers. The INCA method is based on a real-time updated Jacobian model of the control effectiveness, thereby solving an efficient linear control allocation problem. This paper reformulates the original INCA method to optimize the control allocation for minimal propeller power, resulting in more efficient flight. A model predictive control (MPC) controller is added as an actuator dynamics compensation method. This ensures that the commanded control inputs from the INCA controller are achieved. The new controller is compared to a standard incremental nonlinear dynamic inversion (INDI) controller with a translational and rotational loop. It is shown in simulation that by combining INCA with MPC, the tracking performance is improved and efficiency increased by 6.1%.

Files

6.2023_1248.pdf
(pdf | 7.95 Mb)
License info not available