Re-Entry Trajectory Design with Use of Aided Optimization Algorithm through Combination of Classic Guidance & Acceleration Profile Optimization

Abstract

Trajectory optimization is a familiar method for most of re-entry and Re-usable vehicles. This is because of the ability to include almost all of the problem constraints without facing restrictions such as time & calculation issues. Adding or removing constraints in trajectory optimization problem has significant effects on overall optimization performance which even can upgrade the method to an online process. Most of optimization Algorithms such as nonlinear-programming need an initial guess and are also sensitive to it. Hence in this research management of initial guess is done to remove some constraints from optimization problem and transfer them to initial phase. Accordingly an effort is conducted through using a classic guidance method to satisfy constraints of distance error and angle of impact command. The output of guidance initial guess is then fed to the optimization problem. Differential Flatness has been used as a complementary idea to reduce size of optimization problem. 6Dof Simulation results show the increase of optimization performance via reduced number of iterations and Optimization time and increased solution accuracy