Generalized State Estimation for Markovian Coupled Networks Under Round-Robin Protocol and Redundant Channels

Area of Science:

• Control Systems Engineering
• Networked Systems
• Stochastic Systems

Background:

• Investigates generalized state estimation for Markovian coupled networks.
• Addresses challenges like random coupling, packet dropouts, and quantization.
• Considers the round-Robin protocol (RRP) and redundant channels for robust communication.

Purpose of the Study:

• To design an estimator ensuring the extended (Ω1,Ω2,Ω3) - γ -stochastic dissipativity property.
• To enhance the reliability and accuracy of state estimation in complex networked systems.
• To mitigate issues arising from network-induced phenomena.

Main Methods:

• Utilizes an extended dissipative property framework.
• Employs Lyapunov-Krasovskii methodology and Kronecker product.
• Applies an improved matrix decoupling approach and convex optimization.

Main Results:

• Establishes sufficient conditions for the desired extended stochastic dissipativity property.
• Demonstrates the effectiveness of the proposed estimator design.
• Validates the approach through an illustrative example.

Conclusions:

• The proposed method provides a robust solution for state estimation in Markovian coupled networks.
• The integration of RRP and redundant channels enhances network resilience.
• The findings contribute to the advancement of reliable networked control systems.