Distributed event-triggered fractional-order fault-tolerant control of multi-UAVs with full-state constraints

Abstract

This work presents an event-triggered mechanism-based distributed fractional-order fault-tolerant control (FTC) paradigm for multiple unmanned aerial vehicles (multi-UAVs) subject to full-state constraints. Distinct from the existing control solutions for multi-UAVs with constant constraints and symmetric constraints, the time-varying asymmetric constraints considered in this paper are more suitable for practical requirements. Neural networks are exploited to cope with uncertainties arising from unknown nonlinear dynamics. By cleverly combining speed functions with nonlinear state-dependent functions, a novel distributed FTC protocol is established to drive the system states into the boundary functions within a predetermined finite time. Simultaneously, fractional-order calculus is introduced to provide additional adjustment of control parameters, and an event-triggered mechanism is derived to reduce the update frequency of the control signal. It is testified that all signals of each follower UAV are semi-globally uniformly ultimately bounded, and all follower UAVs can follow the attitudes of the leader UAV. In the end, case studies are reported to corroborate the outperformance of the proposed methodology.