Distributed adaptive asymptotically consensus tracking control of uncertain Euler-Lagrange systems under directed...

Area of Science:

• Robotics
• Control Theory
• Systems Engineering

Background:

• Distributed adaptive control is crucial for coordinating multiple uncertain systems.
• Existing methods often require known trajectory models, limiting their applicability.
• Handling unknown trajectories and coupling terms in directed graphs presents significant challenges.

Purpose of the Study:

• To develop a robust distributed adaptive control scheme for uncertain Euler-Lagrange systems.
• To address the challenge of unknown common desired trajectories in subsystems.
• To overcome difficulties associated with asymmetric Laplacian matrices and coupling terms.

Main Methods:

• A backstepping-based control design is employed.
• Smooth functions of consensus errors and positive integrable functions are utilized for virtual control.
• Information exchange of local parameter estimates and adaptive gain techniques are incorporated.
• The control scheme is designed for systems operating under a directed graph.

Main Results:

• The proposed scheme ensures global uniform boundedness of all closed-loop signals.
• Asymptotic output consensus tracking is achieved for the multiple systems.
• The method eliminates the need for linearly parameterized trajectory models.
• It effectively handles unknown trajectory information and coupling effects.

Conclusions:

• The developed distributed adaptive control scheme offers a robust solution for complex multi-system coordination.
• It advances the state-of-the-art in controlling uncertain Euler-Lagrange systems with unknown dynamics.
• The findings have implications for applications requiring coordinated control of multiple robots or agents.