Distributed Adaptive Event-Triggered Fault-Tolerant Consensus of Multiagent Systems With General Linear Dynamics

Area of Science:

• Control Systems Engineering
• Networked Systems
• Robotics

Background:

• Multiagent systems (MASs) are crucial for distributed tasks.
• Fault tolerance and event-triggered control are key challenges in MASs.
• Existing methods often require complex calculations or lack adaptability.

Purpose of the Study:

• To develop a distributed adaptive event-triggered fault-tolerant consensus protocol for general linear MASs.
• To address multiplicative faults and actuator saturation.
• To avoid computationally intensive calculations like determining the minimum eigenvalue of the Laplacian matrix.

Main Methods:

• Design of a distributed event-triggered consensus protocol incorporating adaptive online updating strategies.
• Introduction of adaptive parameters into the trigger function for enhanced self-regulation.
• Derivation of sufficient conditions for leaderless and leader-following consensus.
• Extension of the protocol to handle actuator saturation.
• Proof of avoidance of Zeno behavior.

Main Results:

• A novel distributed adaptive event-triggered consensus protocol is proposed.
• The protocol effectively handles multiplicative faults and actuator saturation.
• The method avoids the need to compute the minimum eigenvalue of the Laplacian matrix.
• Adaptive parameters improve the event-triggered mechanism's self-regulation.
• Zeno behavior is successfully avoided.

Conclusions:

• The proposed distributed adaptive event-triggered fault-tolerant consensus protocol is effective for general linear MASs.
• The method offers improved adaptability and computational efficiency.
• Simulation examples validate the protocol's performance in achieving consensus under fault conditions.