ABSTRACT
To address the difficult control problem for unmanned aerial vehicles against actuator faults and wind effects, a composite decentralized fractional-order backstepping adaptive neural fault-tolerant control method is presented in this chapter for the attitude synchronization tracking of multiple unmanned aerial vehicles, which is integrated with neural networks, disturbance observers, fractional-order calculus, and high-order sliding-mode differentiators. The distinctive feature of this chapter is addressing the attitude synchronization tracking control problem with actuator faults and wind effects in a decentralized framework and proposing a composite approximation method for multiple unmanned aerial vehicles. It is shown that by using Lyapunov methods, the synchronization tracking control is achieved even when multiple unmanned aerial vehicles simultaneously encounter wind effects and actuator faults. Comparative simulation results illustrate the theoretical feasibility.
