The practical application of emerging artificial intelligence (AI) technologies in fields such as computer vision, autonomous driving and robot control has provided important theoretical inspiration and methodological references for the deep technological innovation of morphing aircraft. Compared with traditional aircraft, morphing aircraft have particularities in aspects such as structure and flight modes; consequently, the control challenges they face are more complex and arduous. However, the powerful adaptive learning and complex data processing characteristics of AI technologies precisely provide new ideas for addressing these difficult problems. This paper focuses on reviewing attitude control research that has a crucial impact on the stability and safety of morphing aircraft. We first briefly introduce the definition of morphing aircraft and classify them into four categories according to common types of morphing aircraft, as well as provide the research background and motivation of this paper. Then, the classification of the attitude control method for morphing aircraft is introduced, and the work based on intelligent control methods in the past ten years is focused on sorting out, including fuzzy control, neural network control, and reinforcement learning (RL) control. Finally, the reviewed content is summarized and discussed, and the unresolved issues of morphing aircraft in the attitude intelligent control are discussed and future prospects are explored.
Zhao et al. (2026) studied this question.