Accesso libero

Integrated Fault–Tolerant Control of a Quadcopter UAV with Incipient Actuator Faults

International Journal of Applied Mathematics and Computer Science's Cover Image
International Journal of Applied Mathematics and Computer Science
Big Data and Artificial Intelligence for Cooperative Vehicle-Infrastructure Systems (Special section, pp. 523-599), Baozhen Yao, Shuaian (Hans) Wang and Sobhan (Sean) Asian (Eds.)


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. 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.

Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Mathematics, Applied Mathematics