Revisiting gradient methods in function space with application to rocket trajectories

The gradient method in function space is revisited and applied to the problem of optimizing the trajectories of aerodynamically maneuvering rockets. The optimization objective may be the maximal range or the minimal control effort for a given range. The method is shown to provide an implementable and fast algorithm for a good approximation to the optimal solution. It does not require any non-linear programming solver, and can be straightforwardly programmed in a flight computer. The method can also be used to provide an initial guess for more precise techniques, thus accelerating the computational process.