Optimization control of spacecraft proximation based on r-domination adaptive bare-bones particle swarm optimization algorithm

Abstract

This paper proposes a novel finite-time (FT) optimization control approach of spacecraft proximation based on a new r-domination adaptive bare-bones multi-objective particle swarm optimization scheme (r-ABBMOPSO). Specifically, a new adaptive particle update strategy is developed for bare-bones multi-objective particle swarm optimization algorithm (BBMOPSO) to enhance the robustness of the search. To make the search toward the desired point, r-ABBMOPSO applies r-domination to replace Pareto-domination. In addition, a new adaptive mutation algorithm is designed to strong the population search diversity. By virtue of r-ABBMOPSO to obtain the optimal control parameters, a FT six degrees of freedom (6-DOF) proximation controller with the adaptive update laws of the unknown parameters is proposed to regulate chaser spacecraft approach to target spacecraft. Finally, numerical comparison examples illustrate the performance of the proposed optimization controller.