Adaptive Incremental Nonlinear Control Allocation for the Innovative Control Effectors Aircraft

Master Thesis (2019)
Author(s)

M.J. Mollema (TU Delft - Aerospace Engineering)

Contributor(s)

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

Qiping Chu – Graduation committee member (TU Delft - Control & Simulation)

G La Rocca – Graduation committee member (TU Delft - Flight Performance and Propulsion)

Faculty
Aerospace Engineering
Copyright
© 2019 Michiel Mollema
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Michiel Mollema
Graduation Date
11-10-2019
Awarding Institution
Delft University of Technology
Programme
['Aerospace Engineering']
Faculty
Aerospace Engineering
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Abstract

In this paper an adaptive version of the incremental nonlinear control allocation (INCA), which is able to account for sudden changes in the aerodynamic configuration of an aircraft, is investigated. The controller is designed for the highly maneuverable and tailless innovative control effectors (ICE) aircraft, which has a control suite of 13 nonlinear, interacting and axis-coupled effectors. The least mean squares (LMS) method is used to estimate a delta control effectiveness Jacobian (CEJ) based on the difference between the expected and measured accelerations of the aircraft. This delta CEJ model is then added to the onboard spline CEJ model to achieve fault tolerance. By keeping the nominal spline model intact the nonlinearities and interactions of the effectors remain modeled, while the LMS estimator allows for fast adaptation. Simulations for four different maneuvers and failure cases showed that the estimator is able to stabilize the aircraft for the most demanding maneuver. For two less demanding maneuvers the adaptive controller greatly reduced the control effort while keeping the tracking error similar to the non-adaptive controller. For the remaining fourth maneuver, which operates in a flight region with the most significant interactions and nonlinearities, the adaptive controller had a reduced performance compared to the nonadaptive controller. A sensitivity analysis showed that the choice of design parameters greatly influences the results, and no general set of best performing parameters was found.

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