ABSTRACT
This chapter considers the decentralized fractional-order fault-tolerant control problem for unmanned aerial vehicles against actuator faults and wind disturbances in a directed communication network. A composite adaptive disturbance observer-based decentralized fractional-order fault-tolerant control scheme, which integrates fractional-order sliding-mode surfaces, nonlinear disturbance observers, fuzzy wavelet neural networks, and robust controllers, is developed to achieve the attitude tracking control of unmanned aerial vehicles in a decentralized way. Based on the fractional-order sliding-mode surfaces, the nonlinear disturbance observers are first developed to estimate the lumped uncertainties due to the aerodynamic parameter perturbations, wind disturbances, and actuator faults. Then, adaptive fuzzy wavelet neural networks with updating weighting matrices, mean vectors, and deviation vectors are constructed to effectively attenuate the adverse effects induced by the nonlinear disturbance observer estimation errors. Furthermore, to compensate for the fuzzy wavelet neural network approximation errors, robust controllers are integrated into the developed control scheme to enhance the approximation abilities. It is shown that by using Lyapunov methods, all unmanned aerial vehicles can track their attitude references. Finally, simulation results are presented to demonstrate the effectiveness of the proposed method.
