Observer-based group consensus tracking of hybrid multi-agent systems under adaptive event-triggered mechanism
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View abstract on PubMed
Summary
This summary is machine-generated.This study enhances group consensus tracking in multi-agent systems by optimizing communication resources and improving agent self-adjustment. The adaptive event-triggered mechanism ensures efficient coordination without Zeno behavior.
Area Of Science
- Control Systems Engineering
- Artificial Intelligence
- Robotics
Background
- Multi-agent systems are crucial for coordinating unmanned systems.
- Existing consensus tracking methods face challenges in group division, agent self-adjustment, and communication efficiency.
Purpose Of The Study
- To address limitations in observer-based group consensus tracking for hybrid multi-agent systems.
- To develop an adaptive event-triggered mechanism for enhanced coordination and resource optimization.
Main Methods
- Proposed an improved observation strategy with global observation and clustered cooperative correction terms.
- Designed an adaptive group consensus tracking control protocol using adaptive gain and event-triggered consensus error.
- Implemented an adaptive event-triggered mechanism to prevent Zeno behavior and optimize communication.
Main Results
- Achieved effective group consensus tracking in hybrid multi-agent systems.
- Demonstrated enhanced self-adjustment capabilities for tracking agents.
- Significantly optimized communication resource utilization through the event-triggered mechanism.
Conclusions
- The proposed adaptive event-triggered mechanism effectively solves observer-based group consensus tracking problems.
- The study validates improved system performance and communication efficiency via simulations and comparative experiments.
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