@misc{Kantue_Paulin_Integrated,
 author={Kantue, Paulin and Pedro, Jimoh O.},
 howpublished={online},
 publisher={Zielona Góra: Uniwersytet Zielonogórski},
 language={eng},
 abstract={An integrated approach to the fault-tolerant control (FTC) of a quadcopter unmanned aerial vehicle (UAV) with incipient actuator faults is presented. The framework is comprised of a radial basis function neural network (RBFNN) fault detection and diagnosis (FDD) module and a reconfigurable flight controller (RFC) based on the extremum seeking control approach. The dynamics of a quadcopter subject to incipient actuator faults are estimated using a nonlinear identification method comprising a continuous forward algorithm (CFA) and a modified golden section search (GSS) one.},
 abstract={A time-difference-of-arrival (TDOA) method and the post-fault system estimates are used within the FDD module to compute the fault location and fault magnitude. The impact of bi-directional uncertainty and FDD detection time on the overall FTC performance and system recovery is assessed by simulating a quadcopter UAV during a trajectory tracking mission and is found to be robust against incipient actuator faults during straight and level flight and tight turns.},
 type={artykuł},
 title={Integrated fault-tolerant control of a quadcopter UAV with incipient actuator faults},
 keywords={fault-tolerant control, quadrocopter, incipient actuator fault, radial basis function neural network},
}