Fuzzy adaptive observer–based resilient formation control for heterogeneous multiple unmanned aerial vehicles with false data injection attacks and prescribed performance

This paper addresses the resilient formation control problem for heterogeneous multiple unmanned aerial vehicles (multi-UAV) under false data injection (FDI) attacks and prescribed performance constraints. The case of both actuator and sensor attacks is considered simultaneously, and the multi-UAV can exchange the information through a directed communication network. A fuzzy adaptive observer (FAO) is first proposed to estimate the FDI attacks and the unmeasurable velocity information for each UAV. In order to transform the formation control of heterogeneous multi-UAV into a trajectory tracking control problem of individual UAVs, a bank of distributed estimators is designed to achieve the leader’s states by only using local information among neighboring UAVs. Then, by incorporating a novel tracking error transform method and fractional-order sliding mode control technique, a resilient prescribed performance tracking controller without velocity measurements is constructed. Furthermore, it is proved that all signals of the closed-loop formation control systems are uniformly ultimately bounded (UUB) stable under FDI attacks. Finally, the simulation results are given to verify the effectiveness and superiority of the proposed control strategy.