Adaptive Descriptor Sliding-Mode Observer-Based Dynamic Event-Triggered Consensus of Multiagent Systems Against...

Area of Science:

• Control Systems Engineering
• Robotics
• Networked Systems

Background:

• Multiagent systems (MASs) are susceptible to stability issues caused by common actuator and sensor faults.
• Existing fault-tolerant control (FTC) methods often face challenges in real-time fault diagnosis and communication efficiency.

Purpose of the Study:

• To propose a novel dynamic event-triggered fault-tolerant control (FTC) algorithm for MASs.
• To address concurrent actuator and sensor faults while ensuring system stability.
• To reduce communication overhead through an event-triggered mechanism.

Main Methods:

• Reformulated MAS dynamics into a descriptor form for simultaneous state estimation and fault diagnosis using sliding-mode observers.
• Developed an adaptive FTC algorithm with control gains updated based on observer consensus error.
• Implemented a dynamic event-triggered mechanism for efficient information exchange between agents.

Main Results:

• The proposed descriptor sliding-mode observer effectively estimates states and diagnoses faults.
• The adaptive FTC algorithm successfully maintains MAS stability despite concurrent faults.
• The dynamic event-triggered mechanism significantly reduces communication overhead.

Conclusions:

• The developed dynamic event-triggered FTC algorithm is effective for enhancing MAS stability in the presence of actuator and sensor faults.
• The integration of descriptor observers and adaptive control with event-triggering offers a robust and efficient solution.
• Numerical simulations with quadrotors validate the proposed method's performance.