On-orbit Servicing Mission Planning for Multi-spacecraft Using Improved QPSO Algorithm

The on-orbit servicing mission assignment is very important to improve the cooperative work ratio of the on-orbit servicing spacecraft. One mission of on-orbit servicing can be fulfilled in many ways,and proper mission assignment must be guaranteed. Based on the characteristics and technical specifications of the mission planning issues, a multi-objective quantum-behaved particle swarm optimization based on QPSO and non-dominated sorting (Improved QPSO) is proposed. Since improved QPSO has the characteristic of both QPSO, which has fast convergence rate and accurate convergence value and non-dominated sorting, used to obtain non-dominated solutions, it is used to solve spacecraft task allocation. By analyzing the critical index factors which contain target spacecraft value, task completion time and distance consumption, an on-orbit spacecraft task allocation model is formulated. The best plan was achieved by Pareto optimal sets and ideal solution can be chose as necessary. Finally the example of simulation was given, it compared with another algorithm. Simulation results show that the improved QPSO has fast convergence and better distribution.