Pseudospectral optimal control for trajectory optimization in Aerospace Systems
Pseudospectral optimal control for trajectory optimization in Aerospace Systems
This work involves the implementation of hp-adaptive pseudo-spectral collocation methods for solving nonlinear optimal control problems arising in aerospace trajectory optimization. The approach transcribes continuous-time dynamics and constraints into sparse nonlinear programming problems using global polynomial approximations, with adaptive mesh and polynomial order refinement employed to minimize control approximation error and to resolve solution features that are poorly represented by a single global polynomial. The implemented framework is applied to a range of aerospace scenarios, including entry, descent and landing, ascent, and spacecraft rendezvous, enabling the generation of dynamically feasible, constraint-satisfying optimal trajectories for complex multi-phase missions, including India’s Chandrayaan-3 and upcoming missions such as the Lunar Sample Return, Lunar Polar Exploration Mission, and Mars Landing Mission.
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