As human aeronautic and aerospace technology continues to prosper and the aerial flight space domain further expands, traditional fixed-shape air vehicles have been confronted with difficulties in satisfying complex missions in cross-domain scenarios. Owing to their flexible and deformable appearance, morphing air vehicles are expected to realize cross-domain intelligent flight, thus emerging as the most subversive strategic development trend and research focus in aeronautic and aerospace fields. This paper primarily reviews the research background and challenges of flexible and deformable cross-domain intelligent flight, proposing a corresponding research framework and mode as well as exploring the scientific issues and state-of-the-art solutions, where key research progress is introduced. The explorations covered in this paper also provide ideas and directions for the study of deformable cross-domain intelligent flight, which has critical scientific significance in promoting the study itself.

 Recent advances in Artificial Intelligence (AI) have indicated that inspirations from the brain can effectively improve the level of intelligence for AI computational models, even if just local and partial inspirations. Nevertheless, realizing and exceeding intelligence at a human level still needs a deeper investigation and inspirations from the brain. The goal of brain-inspired intelligence is to achieve human intelligence inspired from brain neural mechanism and cognitive behavior mechanism. To this end, in this paper we introduce the relationship between AI and neuroscience, the current status of brain-inspired intelligence, the future work in intelligent control systems, and its profound influence in other fields.

 In order to improve the safety and reliability of a launch vehicle, we present a reconfigurable guidance method based on online trajectory optimization for thrust decrease at the ascending stage of the launch vehicle in this paper. We used a multiple shooting method to convert the optimal control problem into a nonlinear programming (NLP) problem. Finally, we used the interior point method to solve the NLP problem. The simulation results show that the method can effectively adapt to thrust decreases by 5% and 10%. This reconfigurable guidance method based on online planning is proposed to realize launch missions under the condition of power descent, thus verifying the feasibility of the method.

 As one of the newly developing intelligent/smart materials, shape memory alloys (SMAs) have become an important material and have broad application prospects. With smart structures, the integration of SMAs as actuators and sensors in structural components, has drawn significant attention and interest in the aerospace field. In this paper, the research status of SMAs at home and abroad in recent years was reviewed, including the characteristics, classification, investigation progress and applications in the aerospace field. Finally, the development trend prospects for SMAs was also presented.