Nonfragile Sampled-Data Control for Uncertain Networked Control Systems With Additive Time-Varying Delays

Area of Science:

• Control Engineering
• Systems Science
• Applied Mathematics

Background:

• Networked control systems (NCS) are susceptible to performance degradation due to time-varying delays.
• Uncertainties in NCS models pose significant challenges for controller design.
• Ensuring system stability under these conditions is crucial for reliable operation.

Purpose of the Study:

• To develop a nonfragile sampled-data control strategy for uncertain NCS with additive time-varying delays.
• To guarantee the asymptotic stability of the closed-loop system.
• To provide a robust control solution that accounts for system uncertainties and communication delays.

Main Methods:

• Construction of a Lyapunov-Krasovskii functional (LKF) incorporating additive time-varying delays.
• Application of Jensen's and improved integral inequalities for LKF derivative estimation.
• Formulation of stability conditions using linear matrix inequalities (LMIs).
• Design of a nonfragile sampled-data controller.

Main Results:

• The proposed nonfragile sampled-data control scheme guarantees asymptotic stability for the uncertain NCS.
• The stability conditions are derived in a computationally tractable LMI form.
• The LKF effectively captures the dynamics introduced by time-varying delays.

Conclusions:

• The developed control methodology effectively addresses the stabilization of uncertain NCS with time-varying delays.
• The nonfragile control approach enhances robustness against system uncertainties and delays.
• Numerical examples validate the theoretical findings and demonstrate superior performance compared to existing methods.