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    This study introduces a robust adaptive algorithm to manage time-varying delays and uncertainties in internet-based teleoperation systems. The new method ensures stability and smooth performance, even with network delays and system uncertainties.

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    Area of Science:

    • Robotics
    • Control Systems
    • Networked Systems

    Background:

    • Time-varying delays and system uncertainties are significant challenges in internet-based teleoperation.
    • These factors degrade the stability and performance of robotic manipulator systems.
    • Existing control strategies often struggle to effectively address these combined issues.

    Purpose of the Study:

    • To develop a robust adaptive control algorithm for internet-based teleoperation systems.
    • To effectively mitigate the impact of time-varying delays and system uncertainties.
    • To ensure system stability and smooth operation in practical robotic applications.

    Main Methods:

    • A novel robust adaptive control algorithm was designed to handle time-varying delays and uncertainties.
    • The algorithm provides smooth estimation of delayed reference signals.
    • Chattering-free control torques were generated, enhancing practical applicability.

    Main Results:

    • The proposed algorithm demonstrated effectiveness in managing system uncertainties and time-varying delays.
    • Input-to-state stability was achieved without necessitating high-gain control torques.
    • Experimental simulations using a Phantom Omni Haptic device and UR10 manipulator validated the strategy.

    Conclusions:

    • The robust adaptive algorithm successfully addresses critical challenges in internet-based teleoperation.
    • The control strategy ensures stability and smooth performance, validated through real-time experiments.
    • This work offers a practical solution for reliable remote robotic operations over networks like 4G.