
Research Article
Multi-debris Removal in Low-Orbit Based on Swarm Intelligence Research on Optimal Guidance Method
@INPROCEEDINGS{10.1007/978-3-030-69072-4_10, author={Na Fu and Tian-Jiao Zhang and Lai-Jian Zhou and Yan-Yan Zeng and Chen Zhang}, title={Multi-debris Removal in Low-Orbit Based on Swarm Intelligence Research on Optimal Guidance Method}, proceedings={Wireless and Satellite Systems. 11th EAI International Conference, WiSATS 2020, Nanjing, China, September 17-18, 2020, Proceedings, Part II}, proceedings_a={WISATS PART 2}, year={2021}, month={2}, keywords={Debris removal Path planning Swarm intelligence Global optimization}, doi={10.1007/978-3-030-69072-4_10} }
- Na Fu
Tian-Jiao Zhang
Lai-Jian Zhou
Yan-Yan Zeng
Chen Zhang
Year: 2021
Multi-debris Removal in Low-Orbit Based on Swarm Intelligence Research on Optimal Guidance Method
WISATS PART 2
Springer
DOI: 10.1007/978-3-030-69072-4_10
Abstract
Low-orbit space debris removal path planning can be decomposed into optimization problems of debris removal sequences and optimization of transfer orbit design between debris. In this paper, a two-level planning model is established, and the corresponding group intelligent optimization algorithm is proposed. The upper-level optimization problem takes the debris removal sequence as the design variable, considers the task time constraints, and takes the minimum total task energy consumption as the optimization goal, and uses the discrete ant colony algorithm to solve the optimal debris removal sequence. The lower optimization problem takes the maneuvering time and impulse of the inter-debris transfer orbit mission as the design variables, considers the influence of the earth’s non-spherical perturbation, and adopts the single-circle perturbation Lambert algorithm for the constraint processing method of terminal state satisfaction, and proposes a method based on continuous ant colony. Optimized path planning algorithm. Simulation results show that the strategy and algorithm proposed in this paper are efficient and feasible, which can save fuel to the greatest extent and maximize the benefits of space debris mitigation. The research results of this paper provide technical reserves for the follow-up exploration of the integrated design optimization of debris transfer orbits and debris removal sequences.