Abstract
This paper presents a novel fault tolerant control (FTC) strategy for an unmanned aerial vehicle (UAV) subject to multiple constraints of actuator fault, actuator saturation and external disturbance. First, a radial basis function neural network (RBFNN)-based fault estimation observer is developed to obtain the accurate value of actuator fault. Second, an attitude stabilization FTC approach is established with combining the non-singular fast terminal sliding mode (NFTSM) technology, which could tolerate the estimated loss of effectiveness fault. Third, it is discussed asymptotically stability and stabilization of UAV attitude systems in finite time by Lyapunov method and the improved FTC scheme. Finally, the simulation is carried out to verify the fault tolerant capability of the designed algorithm.
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