Quadrotor UAV predictive maintenance utilizing a two-stage Kalman filter approach
SHEN Fu-yuan
LI Wei
JIANG Dong-nian
MAO Hai-jie
Abstract：In this paper,we propose a method to achieve autonomous maintenance of quadcopter unmanned aerial vehicle(UAV)with multi-actuator degradation by adjusting the weight matrix based on the health-aware body performance state.First,we establish a degradation model for quadrotor UAVs and then construct an autonomous predictive maintenance architecture based on the predictive maintenance and model predictive control strategies.Second,a two-stage Kalman filter method is used to estimate the body state of the UAV and the degradation of each actuator in real-time,and an entropy weighting method is used to fuse the degradation of the four actuators into a comprehensive degradation.Then,we calculate the failure threshold of the UAV based on the Mahalanobis distance health degree and solve the remaining lifetime of the UAV.When the UAV does not satisfy the body performance and time-bound constraints,the weight matrix is adjusted in real-time based on the health degree assessment to achieve autonomous maintenance.Simulation results show that the proposed method can effectively extend the life of the airframe.
Keywords：quadrotor UAVmultiple actuator degradationhealth degreepredictive maintenance
Publication Date：2023-12-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：12( 2265-2276 )