AbstractThis study proposes a multiphase convex programming approach for rapid reentry trajectory generation that satisfies path, waypoint and no-fly zone (NFZ) constraints on Common Aerial Vehicles (CAVs). Because the time when the vehicle reaches the waypoint is unknown, the trajectory of the vehicle is divided into several phases according to the prescribed waypoints, rendering a multiphase optimization problem with free final time. Due to the requirement of rapidity, the minimum flight time of each phase index is preferred over other indices in this research. The sequential linearization is used to approximate the nonlinear dynamics of the vehicle as well as the nonlinear concave path constraints on the heat rate, dynamic pressure, and normal load; meanwhile, the convexification techniques are proposed to relax the concave constraints on control variables. Next, the original multiphase optimization problem is reformulated as a standard second-order convex programming problem. Theoretical analysis is conducted to show that the original problem and the converted problem have the same solution. Numerical results are presented to demonstrate that the proposed approach is efficient and effective.
HighlightsProposed a multi-phase convex optimization for rapid reentry trajectory generation.Formulates a nonlinear and concave dynamic programming problem as a convex problem.Satisfies constraints on heat-flux, dynamic pressure, load, waypoints, and NFZs.
Reentry trajectory optimization with waypoint and no-fly zone constraints using multiphase convex programming
Acta Astronautica ; 137 ; 60-69
2017-04-10
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Steady Glide Reentry Trajectory Optimization with Waypoint and No-fly Zone Constraints
British Library Conference Proceedings | 2016
|Three-Dimensional Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints
Online Contents | 2009
|Pseudospectral Convex Optimization for Reentry Vehicle Guidance with No-Fly Zone Constraints
Springer Verlag | 2022
|