Distributed adaptive fractional-order faulttolerant cooperative control of networked unmanned aerial vehicles via fuzzy neural networks.

Ziquan Yu; Youmin Zhang; Zhixiang Liu; Yaohong Qu; Chun-Yi Su

This study presents a distributed fault-tolerant cooperative control (FTCC) strategy to achieve the attitude synchronisation tracking control of networked unmanned aerial vehicles (UAVs) in the presence of actuator faults and model uncertainties. By utilising the fuzzy neural networks (FNNs), the unknown non-linear terms induced by actuator faults and model uncertainties are estimated as lumped uncertainties. A set of distributed sliding-mode estimators (DSMEs) is then employed to estimate the leader UAV's attitudes for the follower UAVs via a distributed communication network. Based on the estimated knowledge from FNNs and DSMEs, a group of distributed FTCC laws is developed for all follower UAVs by using the fractionalorder calculus. It is proven that with the proposed control scheme, all follower UAVs can track the attitudes of the leader UAV and the tracking errors are uniformly ultimately bounded even when a portion of networked UAVs encounters multiple actuator faults. Comparative simulation results are presented to demonstrate the effectiveness of the proposed approach.

FUZZY neural networks; ATTITUDES of leaders; DRONE aircraft; TELECOMMUNICATION systems; ARTIFICIAL satellite attitude control systems

IET Control Theory & Applications (Wiley-Blackwell), 2019, Vol 13, Issue 17, p2917

1751-8644

Academic Journal

10.1049/iet-cta.2018.6262