Automatic Control System of Electric Aircraft Seats Based on Artificial Intelligence

In response to the demand for comfort and safety control of electric aircraft seats during flight, an artificial intelligence-based seat automatic control system is introduced. The system uses the Deep Q-Network (DQN) to adjust the seat position, angle and support strength in real-time to adapt to different flight conditions and passenger needs, aiming to improve the flight experience and flight safety. First, a personalized adjustment model based on a deep Q-network is used to build a system, and sensors are used to monitor the physiological data of seats and passengers, such as body pressure and position, in real-time to obtain accurate comfort information. Then, a deep Q-network is used to analyze passenger behaviors and preferences and establish a personalized control model. Finally, the system dynamically adjusts various parameters of the seat based on real-time data such as seat position, angle, passenger body position, flight status, as well as historical records such as passenger preferences, seat adjustment mode, flight stage, comfort feedback, etc., to ensure a balance between comfort and safety. This method adjusts strategies in different flight phases (take-off, cruising, landing) to achieve the best human-computer interaction effect. Under standard adjustment, passengers’ comfort scores are mostly concentrated between 7.4 and 7.9, and the safety score of the standard adjustment mode is stable at 94%–96%. In comparison, the personalized adjustment mode significantly improves passenger comfort (8.8–9.3 points), and the safety score is as high as 98%–99%. The AI-based automatic control system for electric aircraft seats has significant advantages in improving flight comfort and safety, and can provide more efficient and personalized seat adjustment solutions for future aviation transportation.