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Related Experiment Videos

Adaptive critic designs for event-based multi-agent systems with asymmetric constraints.

Wenting Yan¹, Ding Wang¹, Xinrui Ma¹

¹School of Information Science and Technology, Beijing University of Technology, Beijing, 100124, China; Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, 100124, China; Beijing Institute of Artificial Intelligence, Beijing University of Technology, Beijing, 100124, China; Beijing Laboratory of Smart Environmental Protection, Beijing University of Technology, Beijing, 100124, China.

Neural Networks : the Official Journal of the International Neural Network Society

|May 19, 2026

Summary

This study introduces an improved event-based distributed control mechanism for nonlinear multi-agent systems, enhancing consensus control with differing leader-follower models and conserving resources via an innovative triggering condition.

Keywords:

Adaptive critic designs Adaptive dynamic programming Event-based control Multi-agent systems Neural networks

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Area of Science:

Control Systems Engineering
Artificial Intelligence
Networked Systems

Background:

Multi-agent systems (MAS) face challenges in achieving consensus, especially with heterogeneous leader-follower model structures.
Resource limitations in communication necessitate efficient control strategies.

Purpose of the Study:

To develop an improved event-based distributed control mechanism for continuous-time nonlinear multi-agent systems.
To address the consensus control problem in MAS with differing leader-follower model structures.
To enhance control efficiency and conserve communication resources.

Main Methods:

Adaptive critic control method
Development of an enhanced control strategy for heterogeneous MAS
Formulation of a non-quadratic function for asymmetric constraints
Introduction of an innovative event-triggered mechanism
Construction of critic neural networks for followers
Lyapunov stability analysis

Main Results:

An improved event-based distributed control mechanism was established.
A novel triggering condition was presented, avoiding Zeno behavior.
Near-optimal control laws were obtained via event-triggered critic neural networks.
Stability of synchronization and weight estimation errors was guaranteed using the Lyapunov method.

Conclusions:

The proposed mechanism effectively achieves consensus control in nonlinear multi-agent systems with heterogeneous models.
The event-triggered approach conserves communication resources and improves control efficiency.
Simulation results validate the effectiveness of the developed control strategy.