Refined fault tolerant tracking control of fixed-wing UAVs via fractional calculus and interval type-2 fuzzy neural network under event-triggered communication

Abstract

The refined fault tolerant tracking control (FTTC) scheme is developed for multiple fixed-wing unmanned aerial vehicles (UAVs) against actuator faults and wind effects under event-triggered communication. To decrease the communication overload caused by the continuous information transmissions among neighboring UAVs, an event-triggered communication mechanism is incorporated to dynamically reduce and increase the triggering frequency at the pre-fault and post-fault phases, respectively, thus reducing the communication burden while ensuring the synchronization tracking performance of faulty UAVs. Moreover, refined FTTC performance with event-triggered communications can be achieved by skillfully invoking fractional-order calculus. Furthermore, interval type-2 fuzzy neural networks with fractional-order adaptive modulation factors are constructed to compensate for the unknown nonlinearities. Lyapunov stability analysis has revealed that all attitudes can synchronously track their references. Simulation results are presented to demonstrate that communication resource-saving refined FTTC performance can be guaranteed with different fractional-order operators.