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

• Published in: International journal of applied mathematics and computer science Vol. 32; no. 4; pp. 601 - 617
• Main Authors: Kantue, Paulin, Pedro, Jimoh O.
• Format: Journal Article
• Language: English
• Published: Zielona Góra Sciendo 01.12.2022; De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
• Subjects: Actuators; Algorithms; Fault detection; Fault diagnosis; Fault location; Fault tolerance; fault-tolerant control; Faults; Flight control systems; Identification methods; incipient actuator fault; Integrated approach; Modules; Neural networks; quadrocopter; Radial basis function; radial basis function neural network; Unmanned aerial vehicles
• ISSN: 1641-876X; 2083-8492; 2083-8492
• DOI: 10.34768/amcs-2022-0042

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.