Distributed prescribed performance containment control for unmanned surface vehicles based on disturbance observer.

Area of Science:

• Robotics and Control Systems
• Marine Engineering
• Distributed Systems

Background:

• Cooperative control of multiple unmanned surface vehicles (USVs) is crucial for complex marine operations.
• Existing methods often struggle with unknown external disturbances and limited communication topologies.
• Ensuring robust containment and tracking performance under uncertainty remains a challenge.

Purpose of the Study:

• To develop a distributed containment control strategy for multiple USVs facing unknown external disturbances.
• To guarantee both transient and steady-state performance for the USV system.
• To ensure all system variables remain bounded and tracking errors are confined within specified ranges.

Main Methods:

• Utilized a fixed, directed communication topology where only some followers can access leader states.
• Introduced new error functions to convert tracking errors for improved performance analysis.
• Employed a disturbance observer to effectively estimate unknown external disturbances.
• Designed a distributed containment controller based on the new error functions and estimated disturbances.
• Applied graph theory and Lyapunov stability analysis to prove system boundedness and error confinement.

Main Results:

• Successfully estimated unknown external disturbances using a disturbance observer.
• Developed a distributed containment controller that accounts for estimated disturbances.
• Proved that all system variables for the multiple USV systems are bounded.
• Demonstrated that tracking errors can be confined within specified performance ranges.
• Simulation results validated the effectiveness of the proposed control strategy.

Conclusions:

• The proposed distributed containment control strategy effectively manages unknown external disturbances in multi-USV systems.
• The controller ensures robust performance, boundedness of system variables, and confinement of tracking errors.
• This research contributes to the advancement of cooperative control for autonomous marine vehicles.