Spacecraft tracking control and synchronization: An assessment of conventional, unconventional, and combined methods

Artificial intelligence (AI) promises breakthroughs in space operations, from mission design planning to satellite data processing and navigation systems. Advances AI transportation have enabled technologies spacecraft tracking control synchronization. This study assesses evaluates three alternative synchronization (TCS) approaches, including non-AI TCS methods, combined methods. The proposes a hybrid model, new model for defining weight coefficients interval type-2 fuzzy sets based compromised solution (IT2FSs-CoCoSo) solve the problem. A methodology is used calculate of criteria, while IT2FSs-CoCoSo applied rank prioritization comparative analysis conducted demonstrate performance proposed model. We present case illustrate applicability exhibit efficacy method prioritizing approaches on ten different sub-criteria, grouped under main aspects, complexity operational efficiency aspects. methods are most advantageous alternative, whereas least advantageous, according findings this study.