Trajectory optimization for accompanying satellite obstacle avoidance

This paper aims at the trajectory optimization problem of an accompanying satellite in the space station under multi-obstacles by model predictive control (MPC) with successive linearization. This optimization problem is reformulated as a mixed integer second-order cone programming (MISOCP) problem by considering the obstacles avoidance, and various physical constraints. More specifically, a novel variation weight cost function is established with the distance information of the accompanying satellite and obstacles, such that a multi-objective optimization performance is achieved by incorporating fuel consumption and time expenditure further. Through the successive linearization of the MPC scheme, the satisfaction of the multiple constraints is established. These results lead to a feasible solution with harsh constraints as well as the fast convergence to the optimal solution. The obstacles avoidance constraints are first implemented through the appropriate selection of initial values, and then solved by successive approximation with the MPC framework for the convergence of solution. Numerical simulation has been conducted to demonstrate the effectiveness and applicability of the proposed method.