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A fixed wing drone cluster is a group of multiple fixed wing drones that work together during flight missions. Compared to individual drones, fixed wing drone clusters have higher comprehensive performance and broader application prospects. However, due to the many risks associated with fixed wing drones operating in harsh environments, such as obstacle collisions, adjacent drone collisions, etc., the safety of drones is threatened. Therefore, a distributed avoidance control system for fixed wing unmanned aerial vehicle clusters based on AI technology was designed. The system hardware unit mainly includes an AI visual sensor design unit, a LiDAR sensor design unit, a controller design unit, and a wireless communication network design unit. Through the above hardware devices, real-time environmental information is provided to control the drone"s flight attitude and achieve information sharing. The software module is based on AI technology to calculate the position and attitude of drones, calculate the position of obstacles to achieve shape perception, and complete distributed avoidance control of drone clusters. Through the collaborative operation of hardware and software, distributed avoidance control of fixed wing drone clusters has been achieved. The experimental results show that the position perception results of the unmanned aerial vehicle and obstacle obtained by the application design system are consistent with the actual position, and the total deviation value of the path is 4m, fully confirming that the design system has better control performance.