State Estimation of Switched Time-Delay Complex Networks With Strict Decreasing LKF

Area of Science:

• Control Systems Engineering
• Network Science
• Nonlinear Systems Analysis

Background:

• State estimation is crucial for switched complex networks (CNs) facing time delays and disturbances.
• Existing methods often employ conservative assumptions, such as the standard Lipschitz condition, limiting applicability.
• Adaptive control strategies are needed for practical, resource-efficient state estimation in complex dynamic systems.

Purpose of the Study:

• To investigate state estimation for switched complex networks with time delays and external disturbances.
• To propose novel adaptive mode-dependent nonidentical event-triggered control (ETC) mechanisms for partial network nodes.
• To develop a less conservative and more practical approach using a discretized Lyapunov-Krasovskii functional (LKF).

Main Methods:

• Utilizing a one-sided Lipschitz (OSL) nonlinear term for a more general model.
• Implementing adaptive mode-dependent nonidentical event-triggered control (ETC) on partial nodes.
• Developing a discretized Lyapunov-Krasovskii functional (LKF) via dwell-time (DT) segmentation and convex combination methods.
• Employing linear matrix inequalities (LMIs) for controller gain design.

Main Results:

• A novel discretized LKF ensures strict monotone decreasing values at switching instants, simplifying L2-gain analysis.
• Adaptive nonidentical ETC mechanisms reduce data transmission and computational load.
• The proposed method is less conservative than traditional approaches.
• Control gains for the state estimator are effectively designed using LMIs.

Conclusions:

• The developed adaptive ETC strategy provides a practical and efficient solution for state estimation in switched complex networks.
• The novel LKF and analysis method reduce conservatism and enhance applicability.
• The results are validated through a numerical example, demonstrating the advantages of the proposed analytical method.