Rule-based safety optimization and dynamical anti-disturbance control: Application to point-to-point transitions for...

Area of Science:

• Robotics
• Control Systems Engineering
• Maritime Autonomous Systems

Background:

• Autonomous surface vehicles (ASVs) face challenges in congested maritime environments.
• Ensuring safety during point-to-point transitions is critical for multi-ASV operations.
• Underactuated ASVs require sophisticated control for reliable navigation.

Purpose of the Study:

• To develop a safety-certified method for point-to-point transitions of multiple underactuated ASVs.
• To enable collision-free navigation while minimizing impact on transition tasks.
• To achieve precise kinetic control without prior ASV model knowledge.

Main Methods:

• A novel rule-based safety optimization approach combined with dynamic anti-disturbance control.
• Kinematic control using nominal guidance laws and rule-based control barrier functions.
• Dynamic control with extended state observers for state estimation and tracking.

Main Results:

• Collision-free point-to-point transitions for multiple ASVs were achieved.
• The control system demonstrated input-to-state stability.
• Safety of the multi-ASV system was mathematically proven and experimentally validated.

Conclusions:

• The proposed rule-based safety optimization and dynamic anti-disturbance control method is effective.
• The approach ensures safe navigation and precise control for ASVs in complex environments.
• This method enhances the reliability of autonomous maritime operations.