Safety-Critical Obstacle Avoidance Control of Autonomous Surface Vehicles with Uncertainties and Disturbances

This paper proposes a safety-critical obstacle avoidance control approach for autonomous surface vehicles (ASVs) with disturbances and uncertainties. The existing exponential control barrier functions (ECBF) are extended to handle unknown disturbances, leading to the development of input-to-state safe exponential control barrier functions (ISSf-ECBFs). An extended state observer is used to estimate unknown external marine disturbances and internal model uncertainties, based on which an anti-disturbance controller is designed. Based on the proposed ISSf-ECBFs, a quadratic programming problem is formulated to determine the optimal control input. It is proven that the closed-loop system is input-to-state safe and the errors of the closed-loop system are uniformly ultimately bounded. Simulations validate the effectiveness of the proposed control strategy.