Adaptive Finite-Time Time-Varying Elliptical Formation Control for a Group of Quadrotors UAVs for Cooperative Wildfire Monitoring

Wildfire suppression is unquestionably one of the most dangerous jobs globally, originating many fatalities each year due to the lack of accurate and timely information about the dynamic spread of wildfires. Uncrewed Aerial Vehicles (UAVs) have been identified as a promising solution that reduces operational expenses considerably and eliminates the need to endanger the lives of human fire observers. This article studies cooperative wildfire surveillance and tracking problem using a group of quadrotor UAVs with system uncertainties. By employing a combination of the non-singular fast terminal sliding mode control (NFTSMC) approach and radial based function neural network (RBFNN), an adaptive finite-time time-varying elliptical formation control framework is designed for a team of quadrotor UAVs to actively monitor the elliptical growth of a wildfire. It is shown that the control framework can guide a group of quadrotor UAVs affected by external disturbances, uncertainties and aerodynamic drag around the perimeter of a wildfire in finite-time. Finally, numerical simulation results have illustrated the efficacy of the proposed control framework.