Application of genetic algorithms to state estimation of tethered systems Original Research Article

The class of intelligent systems tools known as genetic algorithms is applied to the problem of state estimation, specifically, to predict the orbital dynamics of a tethered satellite system. Emphasis here is placed on cases of tethered motion in which only a short arc of observational data is available. For several example cases of tethered system motion, the performance of a genetic algorithm-based method is compared with that of a conventional differential corrections filtering technique. Measures of comparison include orbit determination accuracy, computational speed, and overall ease of use.