Intermediate observers based robust fault estimation for multi-agent systems under communication constraints via...

Area of Science:

• Control Systems Engineering
• Networked Systems
• Fault Diagnosis

Background:

• Multi-agent systems (MASs) face challenges in robust fault estimation due to communication constraints.
• Data packet loss (DPL) is a common issue in the information exchange within MASs, impacting system reliability.

Purpose of the Study:

• To develop a robust fault estimation technique for MASs that accounts for communication constraints and DPL.
• To design an intermediate observer that ensures stability and performance despite information uncertainties.

Main Methods:

• Remodeling MASs as switching systems with a variable sampling strategy to handle DPL.
• Proposing a novel intermediate observer design based on a switching scheme using local agent information.
• Utilizing Lyapunov's criterion and linear matrix inequality (LMI) to derive stability and H∞ performance conditions.

Main Results:

• Sufficient conditions for exponential stability and H∞ performance of the intermediate observer are established.
• The proposed method effectively estimates faults in MASs even with bounded disturbances and DPL.
• Simulation results validate the effectiveness of the developed fault estimation strategy.

Conclusions:

• The novel intermediate observer design provides a robust solution for fault estimation in MASs under communication constraints.
• The method effectively mitigates the impact of data packet loss on fault estimation accuracy.
• This work contributes to the reliable operation of networked control systems facing communication uncertainties.