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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.
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.
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.
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