Dynamic event-triggered tolerant containment control protocol for discrete multiagent systems based on finite index...

Area of Science:

• Control Systems Engineering
• Artificial Intelligence
• Robotics

Background:

• Multi-agent systems require robust control for containment, facing challenges from actuator faults impacting reliability and security.
• Existing control methods often rely on accurate system models, which are difficult to obtain and maintain.
• Actuator faults and energy consumption are critical considerations for practical system deployment.

Purpose of the Study:

• To propose a novel finite index dynamic event-triggered policy iteration algorithm for tolerant containment control.
• To develop a model-free approach that utilizes only input-output data.
• To simultaneously address actuator faults and energy efficiency for improved system performance.

Main Methods:

• A finite index dynamic event-triggered policy iteration algorithm is designed.
• An actor-critic structure with a fault-aware weight tuning law is implemented.
• An event-triggered mechanism is incorporated to optimize computational resource usage.

Main Results:

• The algorithm demonstrates convergence and optimality with a finite number of iterations.
• The proposed method effectively handles actuator faults and reduces energy consumption.
• Simulation results confirm the algorithm's efficiency and practical applicability.

Conclusions:

• The developed algorithm provides a robust and efficient solution for tolerant containment control in multi-agent systems.
• The model-free, fault-aware, and energy-saving approach enhances system reliability and practicality.
• The event-triggered mechanism optimizes computational load, making it suitable for real-world implementation.