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Related Experiment Video

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

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Output Feedback Control and Stabilization for Networked Control Systems With Packet Losses.

Qingyuan Qi, Huanshui Zhang

IEEE Transactions on Cybernetics

|June 2, 2016

Summary

This study addresses optimal control and stabilization for networked control systems (NCSs) facing packet losses. We developed an optimal estimator and controller, establishing conditions for system stability and solvability.

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Area of Science:

Control Theory
Systems Engineering
Stochastic Systems

Background:

Networked control systems (NCSs) present unique challenges due to packet losses.
Traditional control methods struggle with the separation principle and optimal estimation in stochastic systems with multiplicative noise.

Purpose of the Study:

To derive an optimal estimator for NCSs with packet losses.
To design an optimal measurement feedback controller using the maximum principle.
To establish conditions for finite and infinite horizon control and stabilization.

Main Methods:

Derivation of the optimal conditional expectation estimator.
Application of the maximum principle for controller design.
Analysis of asymptotic stability for the estimator.
Introduction of a novel Lyapunov function for infinite horizon analysis.

Main Results:

The optimal estimator and measurement feedback controller for NCSs with packet losses are derived.
Sufficient and necessary conditions for the solvability of finite horizon control problems are presented.
Asymptotic stability of the optimal estimator is proven.
A necessary and sufficient condition for mean square stabilizability in the infinite horizon case is established, linked to an algebraic Riccati equation.

Conclusions:

The proposed methods provide a framework for optimal control and stabilization of NCSs with packet losses.
The findings advance the understanding of control problems in stochastic systems with communication constraints.
The established conditions offer practical criteria for assessing system stability and controller design.