Wind and Actuator Fault Estimation for a Quadrotor UAV Based on Two-Stage Particle Filter

Abstract

This paper investigates the problems of wind and actuator fault estimation for a quadrotor unmanned aerial vehicle (UAV). To effectively assess the safety and reliability of a quadrotor UAV in the presence of unknown wind disturbances, a two-stage particle filter (TSPF) scheme is proposed to obtain the simultaneous estimation of winds and actuator faults that may degrade the performance of the vehicle. In this scheme, the first-stage particle filter is used to estimate the states of the quadrotor UAV, and the second-stage particle filter is designed to produce estimates of unknown parameters, including the wind disturbances and actuator faults. To mitigate the degeneracy and impoverishment issues, the second-stage particle filter admits a parallel implementation of increased particle samplings for the wind and actuator fault estimation. Finally, simulation results are presented to demonstrate the effectiveness of the proposed scheme.