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CEAS EuroGNC 2022 |
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Nonlinear Model Predictive Path Planning with Obstacle Avoidance for an Automated Landing Approach of Fixed-Wing Aircraft |
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Abstract: This work addresses the implementation of a final approach guidance for fixed-wing aircraft using a nonlinear model predictive control concept with collision avoidance capability. This comprises an obstacle identification method using Euclidean clustering and least squares approximation. After the provision of initial trajectories with Dubins paths which consider the flight areas that need to be avoided, the optimal control problem for the landing path is solved using a direct method based on a cost function with suitable penalty criteria. Optimization constraints are determined from flight mechanical limitations, performance requirements and path constraints. Drawbacks of a model predictive guidance are discussed and accounted for by a waypoint tracking strategy in combination with feedforward terms derived from the desired trajectory and the aircraft model. The robustness of the path planning and guidance is investigated with Monte Carlo simulations. | ||||||
Keywords: Nonlinear Model Predictive Control; Automated Landing; Aircraft Control | ||||||
View PDF CEAS-GNC-2022-019 |
Andreas Steinleitner, Yassine Bensaad, Walter Fichter: Nonlinear Model Predictive Path Planning with Obstacle Avoidance for an Automated Landing Approach of Fixed-Wing Aircraft. Proceedings of the 2022 CEAS EuroGNC conference. Berlin, Germany. May 2022. CEAS-GNC-2022-019. |
BibTeX entry: @Incollection{CEAS-GNC-2022-019, authors = {Steinleitner, Andreas and Bensaad, Yassine and Fichter, Walter}, title = {Nonlinear Model Predictive Path Planning with Obstacle Avoidance for an Automated Landing Approach of Fixed-Wing Aircraft}, booktitle = {Proceedings of the 2022 {CEAS EuroGNC} conference}, address = {Berlin, Germany}, month = may, year = {2022}, note = {CEAS-GNC-2022-019} } |