Reconfigurability-optimal design of fixed-wing UAV based on structurally redundant sensor configuration and improved cuckoo search algorithm

To enhance the reliability and fault reconfiguration capability of Unmanned Aerial Vehicles (UAV), this study proposes a reconfigurable optimal design method based on a structurally redundant sensor configuration and an improved cuckoo search algorithm (ICSA). First, the precondition for structural reconfigurability is defined, and a fault reconfiguration matrix, along with a reconfigurability evaluation index, is established to assess system reconfigurability qualitatively. Next, a sensor configuration method is developed to improve structural redundancy, and a minimum structural overdetermined search algorithm is designed to achieve a reconfigurable system. Furthermore, the ICSA enhances the convergence speed and optimization accuracy of the conventional cuckoo search algorithm (CSA) by incorporating a genetic algorithm mutation strategy and adaptive parameter tuning. Based on ICSA, a reconfigurable optimal design strategy is proposed to minimize system design costs while meeting reconfigurability requirements. Simulations on a fixed-wing UAV model validate the rationality and effectiveness of the proposed method. The results demonstrate that the structurally redundant sensor configuration achieves a 100% fault detection rate, 97.14% fault isolation rate, and 96.67% fault reconfiguration rate. Additionally, the ICSA-based approach reduces reconfigurable system design costs by 80% overall and by 8% compared to the unimproved algorithm.