Demonstration And Analysis of The Guiding Control System for Aerospace Crafts

Abstract

The development of space vehicle guidance and control systems gradually becomes a focus in recent research as a key to space vehicles’ information processing and control in the space environment. In general, among the popular methods in G&C systems, artificial intelligence-based algorithms contain a wide prospect. This study offers descriptions of the current methods in AI-based algorithms, proposed challenges involved in this field, and described the recent achievements in solving these issues. To be specific, the basic descriptions of the controlling systems as well as the various state-of-art machine learning approaches that are suitable for the G&C system are demonstrated and analyzed including ANN, DNN, RL, SVM, DRL, etc. According to the analysis, the challenges as well as the drawbacks of the advanced scenarios are estimated as well as propose the future prospects to improve the performance of landing. Overall, these results shed light on guiding further exploration of aerospace vehicles.