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Updated: Mar 8, 2026

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Estimation and LQG Control Over Unreliable Network With Acknowledgment Randomly Lost.

Hong Lin, Hongye Su, Peng Shi

    IEEE Transactions on Cybernetics
    |January 24, 2017
    PubMed
    Summary

    This study addresses networked control systems with random packet loss, developing a suboptimal linear quadratic Gaussian (LQG) controller for improved stability and performance despite communication challenges.

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    Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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    Area of Science:

    • Control Systems Engineering
    • Networked Systems
    • Signal Processing

    Background:

    • Networked control systems (NCS) face challenges due to random data loss in control inputs, observations, and acknowledgments.
    • Packet loss significantly impacts system performance and stability, necessitating robust control strategies.

    Purpose of the Study:

    • To investigate state estimation and linear quadratic Gaussian (LQG) control for NCS with random packet loss.
    • To address the computational intractability of optimal LQG control in such systems.
    • To design and validate a suboptimal LQG controller that ensures closed-loop stability.

    Main Methods:

    • Derivation of an optimal estimator with exponentially increasing terms.
    • Development of a suboptimal estimator using gains from the optimal estimator.
    • Design of a suboptimal LQG controller and establishment of stability conditions.

    Main Results:

    • The optimal estimator for NCS with packet loss was obtained.
    • Optimal LQG control was found to be computationally prohibitive and unnecessary in general.
    • A stable suboptimal LQG controller was successfully designed and validated through examples.

    Conclusions:

    • Suboptimal LQG control provides a feasible and effective solution for NCS with random packet loss.
    • The proposed controller design ensures closed-loop system stability.
    • The developed methods offer practical advantages for real-world networked control applications.