Optimizing control efficiency in discrete-time multi-agent systems via event-triggered containment techniques...

Area of Science:

• Control Systems Engineering
• Networked Systems Theory

Background:

• Multi-agent systems face challenges with disturbances and input delays.
• Optimizing controller actuation updates is crucial for system performance.
• Resource-constrained environments necessitate efficient control strategies.

Purpose of the Study:

• To mitigate disturbances and input delays in discrete-time multi-agent systems.
• To optimize controller actuation updates using an event-triggered confinement control system.
• To address containment control issues in resource-constrained scenarios.

Main Methods:

• Implementation of a decentralized and centralized event-triggered control system.
• Application of matrix theory and Lyapunov techniques for convergence analysis.
• Development of an event-triggered condition for follower adjustments.

Main Results:

• Successfully mitigated disturbances and input delays.
• Optimized controller actuation updates for efficiency.
• Demonstrated freedom from Zeno phenomena through convergence analysis.
• Validated theoretical results using numerical simulations.

Conclusions:

• The proposed event-triggered confinement control system effectively manages multi-agent systems under disturbances and delays.
• The strategy is particularly beneficial for resource-constrained environments.
• The approach ensures system stability and avoids Zeno phenomena.