Adaptive Event-Triggered Consensus Control of a Class of Second-Order Nonlinear Multiagent Systems

Area of Science:

• Control Engineering
• Systems Science
• Network Science

Background:

• Multiagent systems (MASs) are crucial for distributed tasks.
• Achieving consensus in nonlinear MASs with unknown dynamics is challenging.
• Event-triggered control aims to reduce communication load in MASs.

Purpose of the Study:

• To develop an adaptive event-triggered consensus control scheme for second-order nonlinear MASs.
• To improve control performance and network communication efficiency.
• To design self-triggered algorithms that eliminate continuous monitoring.

Main Methods:

• An adaptive distributed event-triggered consensus control scheme using an auxiliary state.
• Adaptive regulation of the triggered function's coefficient based on auxiliary state error.
• Development of two self-triggered algorithms for known and unknown system functions.
• Rigorous stability analysis of the closed-loop system.

Main Results:

• The proposed scheme ensures bounded signals in the closed-loop system.
• Zeno behavior is successfully excluded, guaranteeing practical implementation.
• Adaptive control improves both system performance and communication efficiency.
• Simulation examples validate the theoretical findings.

Conclusions:

• The novel adaptive event-triggered consensus control is effective for nonlinear MASs.
• The self-triggered algorithms offer efficient alternatives to continuous monitoring.
• The approach enhances stability and prevents Zeno behavior in MASs.