Trajectory tracking control of hovercraft in marine environments with asymmetric error constraints and actuator dead zones

Hovercrafts operating in complex marine environments are subject to asymmetric navigation constraints, actuator dead zones, and external disturbances. This paper proposes an asymmetric prescribed performance control framework for trajectory tracking under these challenges. A novel error transformation enforces asymmetric tracking bounds without modifying the prescribed performance function. An RBF neural network-based lumped disturbance observer is developed to estimate model uncertainties, environmental disturbances, and dead-zone nonlinearities online. The proposed controller integrates asymmetric performance enforcement and dead-zone compensation within a unified structure. Lyapunov analysis proves the boundedness of all closed-loop signals and guarantees satisfaction of the prescribed asymmetric error constraints. Simulation results show that the proposed method improves tracking accuracy and robustness while reducing control oscillations under complex disturbances.