Improved result on state estimation for complex dynamical networks with time varying delays and stochastic sampling...

Area of Science:

• Control Theory
• Network Systems
• Dynamical Systems

Background:

• Complex dynamical networks (CDNs) are crucial in various fields.
• Time-varying delays pose significant challenges in state estimation.
• Sampled-data control offers a practical approach for networked systems.

Purpose of the Study:

• To develop a robust state estimator for CDNs with time-varying delays.
• To address challenges introduced by stochastic sampling periods.
• To ensure stability and performance of the estimation system.

Main Methods:

• Utilizing sampled-data control and an input-delay approach.
• Transforming the system into a continuous time-delay system with stochastic parameters.
• Constructing a Lyapunov-Krasovskii functional (LKF) with integral terms.
• Applying Wirtinger-based and Jensen integral inequality techniques.

Main Results:

• Established delay-dependent stability conditions for the state estimator.
• Demonstrated the effectiveness of the proposed method through a numerical example.
• The developed conditions are solvable using MATLAB's LMI toolbox.

Conclusions:

• The proposed state estimation scheme is effective for CDNs with time-varying delays.
• The method provides a robust framework for handling stochastic sampling periods.
• This work contributes to the advancement of control and estimation in complex networked systems.