This study deals with the robust optimization of
the transition maneuver for a vertical take-off
and landing drone (VTOL) using a bi-level
optimal control (OC) approach: The upper level, parameter optimization, problem is optimized
using a differential evolution (DE) genetic
algorithm. By this a global optimal solution is
achieved.
On the other hand, the lower level problem
is solved by using a gradient-based direct OC
scheme. The distinctiveness of this lower
level setup is the fact that not only the general
mean optimization problem is solved, but an
OC problem (OCP) with uncertainties. This
combination yields the possibility to calculate
robust trajectories.
The uncertainty modeling is done by means of
generalized polynomial chaos (gPC). Thus, the
lower level problems are not only solved at one
specific set of parameters, but on multiple parameter
sets to calculate the uncertainty influence
on the optimal trajectory in distinct parameters.
The developed algorithm is applied to the
transition maneuver, including the climb to
a safe altitude, of a VTOL. The results show
an enhancement of the optimal trajectory in
the sense of robustness with respect to wind
influences regarding the safety of the transition
maneuver.
«
This study deals with the robust optimization of
the transition maneuver for a vertical take-off
and landing drone (VTOL) using a bi-level
optimal control (OC) approach: The upper level, parameter optimization, problem is optimized
using a differential evolution (DE) genetic
algorithm. By this a global optimal solution is
achieved.
On the other hand, the lower level problem
is solved by using a gradient-based direct OC
scheme. The distinctiveness of this lower
level...
»