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    A new hybrid event-triggered (ET) control framework optimizes tracking in nonlinear networked control systems. This method conserves network resources by using adaptive critics and reducing continuous triggering, enhancing system stability.

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    Area of Science:

    • Control Systems Engineering
    • Networked Systems
    • Nonlinear Dynamics

    Background:

    • Networked control systems (NCS) face challenges with limited bandwidth and stability.
    • Optimal tracking is crucial for many NCS applications.
    • Traditional event-based control requires continuous condition evaluation, consuming resources.

    Purpose of the Study:

    • To develop a novel hybrid event-triggered (ET) control framework for discrete-time nonlinear NCS.
    • To address the optimal tracking problem while conserving network resources.
    • To ensure the stability of the error system.

    Main Methods:

    • Constructed an augmented plant by combining system state and reference trajectory.
    • Developed a hybrid ET mechanism with a constant interval for event silence.
    • Implemented an online adaptive critic algorithm using model, critic, and action networks.

    Main Results:

    • Transformed the optimal tracking problem into an optimal regulation problem.
    • Alleviated limited network bandwidth and eliminated continuous triggering condition evaluation.
    • Demonstrated real-time adjustment of the tracking control policy to optimal levels.

    Conclusions:

    • The proposed hybrid ET control framework effectively addresses optimal tracking in nonlinear NCS.
    • The method conserves network resources and enhances system stability.
    • The adaptive critic technique enables real-time optimization of the control policy.