Disturbance observer-based prescribed performance super-twisting sliding mode control for autonomous surface vessels.

Area of Science:

• Marine Engineering
• Control Systems Theory
• Robotics

Background:

• Autonomous Surface Vessels (ASVs) require robust control for trajectory tracking.
• Unknown external disturbances and modeling errors significantly degrade ASV control performance.
• Existing control methods often struggle with precise trajectory following and exhibit chattering.

Purpose of the Study:

• To develop an advanced control strategy for ASVs to achieve precise trajectory tracking.
• To mitigate the impact of unknown external disturbances and system modeling errors on ASV control.
• To ensure improved transient performance and practical applicability through a chatter-free controller.

Main Methods:

• A disturbance observer (DOB) is employed to approximate and compensate for lumped disturbances.
• A prescribed performance super-twisting sliding mode controller (PPSTSMC) is designed to handle residual errors.
• The controller incorporates prescribed performance constraints to manage transient system behavior.

Main Results:

• The proposed DOB PPSTSMC effectively compensates for unknown external disturbances and modeling errors.
• The controller ensures accurate tracking of time-varying trajectories for ASVs.
• Simulation results demonstrate superior transient performance and robustness compared to other methods.

Conclusions:

• The DOB PPSTSMC offers a robust and effective solution for ASV trajectory tracking under uncertainties.
• The method significantly improves both steady-state and transient control performance.
• The continuous and chatter-free nature of the controller enhances its practical implementation value.