The ascent prediction of zero-pressure balloons plays a crucial role in campaigns involving drop and reentry tests. This paper introduces a data-driven approach to estimating the balloon ascent. An output-constrained fuzzy clustering technique is used to develop a fuzzy model for the ascent of zero-pressure balloons using field data from the previous campaigns performed at the Esrange Space Center of the Swedish Space Corporation in Kiruna. The fuzzy model is verified by performing a root-mean-square analysis of the estimated ascent against the real ascent trajectories from test data sets.
展开▼
