Actuator Fault Tolerant Control based on Neuroadaptive SMC for Quadrotor UAVs

This paper designs a fault tolerant control (FTC) algorithm for quadrotor UAV with actuator failure. The algorithm combines the advantages of radial basis function(RBF) neural network and adaptive sliding mode control(SMC), which has advantages in dealing with uncertainties and external disturbances in quadrotor systems and featured with simplicity. The dynamic equation including external disturbance is established by Newton-Euler theorem. The RBFNN is used to approximate uncertainties and time-varying external disturbances. Consequently, this scheme allows avoiding high precision of system modeling, solve the chattering problem of SMC, and guaranteeing the stability and robustness. The stability of this scheme analysed by Lynapunov theory and verified by simulation results
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