UAV trajectory optimization using chance-constrained second-order cone programming

It is challenging to generate optimal trajectories for nonlinear dynamic systems under external disturbances. In this brief, we present a novel approach planning safe of the chance-constrained trajectory optimization problems with nonconvex constraints. First, chance constraints are handled by deterministic ones which show its availability. We derive an iterative convex method solve control problem. Then (CCOCP) problem reformed be programming (NLP) through hp-adaptive pseudospectral method. An successive linearization algorithm detailed NLP one described as second-order cone demonstrate proposed on 3-DoF unmanned aerial vehicle system chance-constrained. The simulation results reliable solutions UAV