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Related Experiment Video

Updated: Apr 26, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Improved stabilization method for networked control systems with variable transmission delays and packet dropout.

Arash Farnam¹, Reza Mahboobi Esfanjani¹

¹Electrical Engineering Department, Sahand University of Technology, Tabriz, Iran.

ISA Transactions

|July 19, 2014

Summary

This study enhances networked control system (NCS) stability analysis and stabilization by introducing a novel Lyapunov-Krasovskii functional to address network delays and data dropouts effectively.

Keywords:

Linear matrix inequality (LMI)Lyapunov–Krasovskii theorem Networked control systems Stabilization

Related Experiment Videos

Last Updated: Apr 26, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Area of Science:

Control Engineering
Systems Science
Computer Engineering

Background:

Networked control systems (NCS) face challenges from network-induced delays and data dropouts, impacting stability.
Existing methods for NCS stability analysis and stabilization can be conservative.

Purpose of the Study:

To develop a less conservative method for stability analysis and stabilization of NCS with network-induced delay and data dropout.
To design a memoryless state-feedback controller for improved NCS performance.

Main Methods:

Introduction of a novel augmented Lyapunov-Krasovskii functional.
Employment of new free-weighting matrices to enhance flexibility in stabilizability conditions.
Computation of controller gain using linear matrix inequalities (LMIs).

Main Results:

The proposed method yields less conservative results compared to existing approaches.
The designed controller effectively stabilizes the networked control system.
Illustrative examples confirm the method's applicability and superior performance.

Conclusions:

The novel approach provides an effective and less conservative solution for NCS stability and stabilization.
The use of augmented Lyapunov-Krasovskii functionals and free-weighting matrices is beneficial for NCS control.
The LMI-based controller design is practical and outperforms existing methods.