• Aucun résultat trouvé

On the minimum time optimal control problem of an aircraft in its climbing phase

N/A
N/A
Protected

Academic year: 2021

Partager "On the minimum time optimal control problem of an aircraft in its climbing phase"

Copied!
15
0
0

Texte intégral

Loading

Figure

Table 1: Constant data of a middle-haul aircraft and constant data of the atmospheric model during the climbing phase.
Figure 2: Evolution of the altitude h and of the true air speed v associated to the σ − σ s σ + structure
Figure 4: Evolution of the quantities α(·), β(·) and D 0 (x(·)) D 101 (x(·)) along the singular arc
Figure 5: Evolution of Λ(·) = det( f 0 (x(·)), f 1 (x(·)), J(·)) on [t 1 ∗ , t 2 ∗ ] where J(·) represents the Jacobi field
+4

Références

Documents relatifs

Generating optimal aircraft trajectories with respect to weather conditions?. Brunilde Girardet, Laurent Lapasset,

Furthermore, since the anesthesia model presents multiple time scale dynamics that can be split in two groups : fast and slow and since the BIS is a direct function of the fast ones,

In [4], Ng extended Jardin’s work and developed a trajectory optimization algorithm for minimizing aircraft travel time and fuel burn by combining a method for computing

Specimens (swab samples [swab], punch biopsy tissue specimens [tissue-punch], and surgically excised tissue specimens [tissue-surgery]) obtained from 384 patients with suspected

We give in this section some preliminary results on the structures of the trajectories for two different problems: α = 1 (minimum time problem) and α = 0.6 , for a medium-haul

First, we introduce a reduced-order problem with affine dynamics with respect to the control and analyze it with the tools from geometric control: maximum principle combined with

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

The situation is analogous to the one in Riemannian geometry with cut and conjugate points: Up to some point, the path provides minimizers; then global optimality is lost