Event-triggered leader-following tracking control for multivariable multi-agent systems (1603.04125v1)

Abstract: The paper considers event-triggered leader-follower tracking control for multi-agent systems with general linear dynamics. For both undirected and directed follower graphs, we propose event triggering rules which guarantee bounded tracking errors. With these rules, we also prove that the systems do not exhibit Zeno behavior, and the bounds on the tracking errors can be tuned to a desired small value. We also show that the combinational state required for the proposed event triggering conditions can be continuously generated from discrete communications between the neighboring agents occurring at event times. The efficacy of the proposed methods is discussed using a simulation example.

• The paper introduces event-triggered control rules that guarantee bounded tracking errors in multivariable multi-agent systems using adjustable triggering conditions.
• It presents a novel combinational state generation technique to compute essential state information during discrete communication events, reducing continuous monitoring.
• Numerical simulations confirm the method’s efficiency by achieving tracking errors as low as 0.05 while drastically cutting down communication requirements.

Event-Triggered Leader-Following Tracking Control for Multivariable Multi-Agent Systems

The paper "Event-triggered leader-following tracking control for multivariable multi-agent systems" introduces a novel approach to address the leader-following control problem in multi-agent systems. This paper focuses on event-triggered control methodologies, which significantly reduce communication requirements compared to continuous monitoring approaches, thus enhancing the practicality and efficiency of deploying multi-agent systems, especially in constrained environments.

Overview of Contributions

The key contributions include the formulation of event triggering rules that ensure bounded tracking errors in multi-agent systems characterized by general linear dynamics. The research thoroughly examines systems modeled by undirected and directed graphs, enhancing its applicability across different network topologies.

Technical Insights

Event Triggering Conditions:

The paper establishes specific event triggering rules, ensuring that multi-agent systems effectively achieve leader-following synchronization without Zeno behavior, where Zeno behavior refers to the occurrence of an infinite number of triggering events in a finite time period. The results demonstrate how tracking precision can be finely tuned by adjusting the triggering condition parameters, allowing for control strategies adaptable to various system dynamics and communication constraints.

Combinational State Generation:

A significant innovation lies in the combinational state generation, which allows for the continuous computation of necessary state information across discrete communication events without requiring constant monitoring—a marked improvement in efficiency for distributed systems.

Numerical and Theoretical Findings

Numerical simulations underscore the proposed method's ability to achieve desired tracking precision while minimizing communication load. The numerical results show that by tuning certain parameters, the system can maintain bounded tracking errors as low as 0.05. Furthermore, the research explores solving Riccati inequalities and leveraging LMI solvers to determine optimal control matrix configurations, offering robust guidelines for practical application in diverse network configurations.

Implications and Future Directions

The practical implications of this paper suggest an impactful reduction in communication overhead for multi-agent systems, which is particularly advantageous for networks with limited bandwidth or energy resources. Theoretical implications highlight advancement in decentralized control approaches for systems with general linear dynamics. Future research could explore extending these methodologies to nonlinear systems or address dynamic topology changes, thereby widening the applicability and robustness of event-triggered control systems in unpredictable environments.

Conclusively, this paper provides a comprehensive framework for understanding and implementing event-triggered controls for leader-following multi-agent systems, laying groundwork for future exploration in the domain of efficient and robust system synchronization protocols.