Multiple UAV Cooperative Substation Inspection: A Robust Fixed-Time Group Formation Control Scheme

This study investigates the cooperative substation inspection problem for multi-unmanned aerial vehicle systems (MUAVs) subjected to uncertain disturbances. To enhance inspection reliability and efficiency, a novel distributed fixed-time group consensus control scheme is proposed. In this framework, radial basis function neural networks (RBF NNs) are employed to approximate both intrinsic nonlinear uncertainties and uncertain disturbances affecting UAV dynamics. Subsequently, a distributed fixed-time controller is developed via backstepping techniques, where fixed-time command filters are integrated to circumvent the complexity explosion inherent to conventional backstepping. Furthermore, an approximation error compensation system is established. It mitigates estimation inaccuracies arising from RBF NN approximations and command filtering processes. The mathematical analysis demonstrates that the proposed controller ensures the fixed-time convergence of group consensus errors into an adjustable residual set. Finally, numerical simulations and MUAV group formation simulations validate the robustness against aerodynamic uncertainties.