Smart leader-based distributed active anti-disturbance hybrid consensus control for multi-agent systems with...

Area of Science:

• Robotics and Control Systems
• Distributed Systems and Artificial Intelligence

Background:

• Multi-agent systems (MAS) struggle with consensus tracking under external disturbances, especially in leader-follower setups.
• Static leaders in traditional MAS lack adaptability and effective disturbance rejection.
• Achieving robust consensus tracking requires advanced control strategies for dynamic environments.

Purpose of the Study:

• To propose a novel smart leader-follower hybrid control framework for MAS.
• To enhance adaptability, robustness, and disturbance rejection capabilities in consensus tracking.
• To reduce communication costs and improve system efficiency and scalability.

Main Methods:

• A smart leader dynamically adjusts control using self-triggered impulsive neighbor information.
• Followers utilize self-triggered impulsive feedback combined with feedforward control via a linear extended state observer (LESO).
• The framework integrates dynamic self-triggering and LESO for real-time disturbance compensation.

Main Results:

• The proposed framework significantly reduces tracking errors and enhances system cohesion.
• The smart leader's dynamic adjustments improve followers' error system eigenvalues for faster tracking.
• LESO effectively compensates for real-time disturbances, demonstrating strong disturbance rejection capabilities.
• Simulations validate the framework's efficiency, robustness, and scalability.

Conclusions:

• The smart leader-follower hybrid control framework offers a significant advancement for MAS consensus tracking.
• The integration of self-triggered impulsive control and LESO provides superior adaptability and disturbance rejection.
• This approach presents a flexible, efficient, and scalable solution for complex multi-agent coordination problems.