Sliding Mode Fault Tolerant Control for a Quadrotor with Varying Load and Actuator Fault

In this paper, an adaptive sliding mode fault-tolerant control scheme based on prescribed performance and neural networks is developed for Unmanned Aerial Vehicle (UAV) quadrotor carrying a load to deal with actuator faults. First, nonsingular fast terminal (NFTSM) strategy presented. virtue of the proposed strategy, convergence high robustness can be guaranteed without stimulating chattering. Secondly, obtain correct fault magnitudes compensate failures actively, radial basis function network-based estimation proposed. By combining NFTSM controller, active algorithm established. Then, uncertainties caused by variation are explicitly considered compensated presented laws. Moreover, synthesizing (PPC), output error transformation defined state constraints provide better tracking performance. From Lyapunov stability analysis, overall system proven uniformly asymptotically stable. Finally, numerical simulation helicopter carried out validate effectiveness superiority algorithm.