Multi-objective optimization for robust attitude determination of satellite with narrow bound theory - Yang, Chen; Liu, Yinde (Advances in space research, 2024)
This work develops a novel multi-objective optimization for a robust attitude determination method using the narrow bound theory, which is more appropriate to the limited uncertain samplings. The classical Wahba problem for determining attitude is expanded into the framework of the interval uncertainty theory to comply with the complex environment of actual space. Since on-orbit data samples are limited and it is inconvenient to quantify uncertainty using probabilistic and statistical methods, this paper quantifies various incomplete information of the attitude determination system into unknown-but-bounded (UBB) numbers. As long as the limited ranges of uncertainties or errors are identifiable, these uncertainties will be precisely quantified in the overall attitude determination. To overcome the overestimation defect caused by interval perturbation analysis theory, this study designed a narrow bound theory originated from polynomial chaos expansions, that is, the boundary determined by interval dimension-wise analysis (IDWA) with accurate estimated bounds of attitude determination. An advanced multi-objective optimization algorithm (SPEA/R) is used to address the minimum nominal value and minimum fluctuation of the uncertain attitude determination problem, and the efficiency of this method is validated through a numerical example.