Event-Triggered Robust Control for Output Consensus of Unknown Discrete-Time Multiagent Systems With Unmodeled...

Area of Science:

• Control Theory
• Systems Engineering
• Robotics

Background:

• Multiagent systems (MAS) are crucial for distributed tasks.
• Achieving consensus in MAS with unknown dynamics and unmodeled perturbations is challenging.
• Event-triggered control reduces communication load in MAS.

Purpose of the Study:

• To investigate the event-triggered output consensus problem for unknown heterogeneous discrete-time linear MAS.
• To develop a novel distributed control framework for MAS with unknown parameters and unmodeled dynamics.
• To guarantee system stability and consensus error convergence under specific conditions.

Main Methods:

• A novel design framework combining an event-triggered internal reference model and a distributed model reference adaptive controller.
• Dynamic event-triggering mechanism to minimize communication.
• Robust model reference adaptive control to handle unknown parameters and multiplicative perturbations.

Main Results:

• The proposed framework guarantees boundedness of all signals and convergence of consensus errors to a residual set under certain conditions.
• Consensus errors converge asymptotically to zero in the absence of unmodeled dynamics.
• The framework is fully distributed, requiring no global information.

Conclusions:

• The developed framework effectively addresses output consensus in unknown heterogeneous discrete-time linear MAS with unmodeled dynamics.
• The event-triggered approach reduces communication burden while maintaining system performance.
• The method's applicability and robustness are validated through examples.