A health performance evaluation method of multirotors under wind turbulence

As an unmanned system, the multirotor has gained widespread attention in practical aviation engineering, because of its ease of use, reliability and maintainability. From the perspective of flight reliability and safety, it is significant and essential for a multirotor to detect anomaly occurrences and evaluate the real-time health performance status in a timely manner. Considering the limitations in the modeling of multirotor dynamics and the state estimation of existing methods, a health performance evaluation method of multirotors under wind turbulence is proposed in this paper. First, a stochastic hybrid system (SHS)-based model is established to describe the dynamic behavior of the multirotor, where the flight dynamics, external disturbances due to wind turbulence, and dynamics of discrete modes are included. The real-time probability distribution of the hybrid state of the SHS-based multirotor model is obtained by a modified interacting multiple model particle filter algorithm. Based on this, the real-time overall health performance status of the multirotor during flight is quantitatively evaluated by the classical health degree and the fuzzy health degree as indicators. Finally, a multirotor suffering from different types of sensor anomalies is simulated to demonstrate the availability and effectiveness of the proposed method.