Robust adaptive persistent coverage control for multi-UAV systems under unknown environmental disturbances

Purpose This study aims to address the problem of safe persistent coverage in multi-UAV systems under the combined effects of unknown environmental disturbances and dynamic obstacles. Design/methodology/approach A multi-UAV dynamics model containing unknown disturbances is established, and a high-gain disturbance observer is designed to achieve online disturbance estimation. Furthermore, an adaptive safe distance mechanism based on relative velocity is constructed, and the upper bound of the disturbance estimation error is embedded into control barrier function (CBF) constraints to form robust safety constraints. Coverage optimization and safety-preserving control are integrated into a unified constrained optimization framework. Findings Simulation results demonstrate that the proposed method effectively guarantees obstacle avoidance safety under unknown environmental disturbance conditions. It significantly improves the persistent coverage performance, trajectory tracking capability and overall robustness of the multi-UAV system. Originality/value This study integrates feedforward disturbance compensation with adaptive robust CBFs within a unified constrained optimization framework. By using a time-varying estimation-error bound that converges to an ultimate bound, the safety constraints can be gradually adjusted as the disturbance estimation error decreases, thereby avoiding unnecessary conservatism while resisting environmental disturbances without requiring accurate obstacle motion models.