A Configuration Optimization Method of Integrating Concentrating & Migration Genetic Algorithm for Cellular Reconfigurable Spacecrafts

The cellular reconfigurable spacecraft has been highly concerned as a flexible and cheaper space system. To obtain a suitable and optimal configuration scheme for our work, a novel configuration optimization method is proposed in this paper. Firstly, three-level module management architecture is built for the configuration design of cellular reconfigurable spacecraft, which can realize the free definition of modules. Afterwards, by designing the performance index suitable for our task requirements, the configuration design issue is modeled as an optimal problem. Due to the limitation of existing solutions, a novel genetic algorithm is developed by drawing inspiration from the concentrating & migration behavior in wildebeest population. And then, based on all above works, a configuration optimization method based on the concentrating & migration genetic algorithm is presented. The simulation result shows that the presented method can obtain an assembly configuration with better moment of inertia and smaller envelope filling ratio. That is to say, the overall performance of configuration is better.