Ascent Trajectory Optimization of Launch Vehicle Using Controlled Random Search

Ascent trajectory optimization is the process of finding optimal trajectory of a launch vehicle during its ascent to space. Optimization problem involves maximising or minimising various objective functions while satisfying various constraints. In this paper, we are designing an optimal trajectory of a launch vehicle during the ascent phase to minimise the fuel consumption and to obtain maximum velocity at desired altitude using controlled random search (CRS). The ascent trajectory optimization is then compared with Random Search (RS). RS generates random points within the defined bounds for the control variables and selects the one which has highest function value, while in CRS, the algorithm generates new points by adding a random perturbation to the worst point, rather than generating completely new random points. By comparing RS and CRS, we can find which trajectory optimization method is efficient. The simulation results highlights the significant performance improvement of CRS.