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Event-Triggered-Based Distributed Consensus Tracking for Nonlinear Multiagent Systems With Quantization.

Jing Zhang, Shuai Liu, Xianfu Zhang

    IEEE Transactions on Neural Networks and Learning Systems
    |June 23, 2022
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    Summary
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    This study introduces an adaptive neural network (NN) approach for distributed consensus tracking in nonlinear multiagent systems. The method reduces data transmission using event-triggered mechanisms and quantizers, ensuring reliable tracking without Zeno behavior.

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    Area of Science:

    • Control Systems Engineering
    • Artificial Intelligence
    • Networked Systems

    Background:

    • Addressing limited communication capacity in multiagent systems is crucial.
    • Nonlinear dynamics and unmeasurable states pose challenges in distributed control.
    • Quantization effects can degrade system performance and stability.

    Purpose of the Study:

    • To investigate an observer-based adaptive neural network (NN) event-triggered distributed consensus tracking strategy.
    • To handle nonlinearities and unmeasurable states in multiagent systems with communication constraints.
    • To develop a control protocol that mitigates Zeno behavior.

    Main Methods:

    • Utilizing an event-trigger mechanism and dynamic uniform quantizers to minimize information exchange.
    • Employing adaptive neural networks (NNs) to approximate unknown nonlinear functions.
    • Designing an NN-based state observer with a dynamic gain function for state estimation.
    • Developing a distributed control protocol that accounts for coupled effects of event-triggered conditions and quantization.

    Main Results:

    • The proposed control protocol ensures distributed consensus tracking for nonlinear multiagent systems.
    • The strategy effectively reduces information transmission while maintaining system performance.
    • Zeno behavior is successfully avoided through the designed control framework.
    • Simulation results validate the effectiveness of the developed control protocol.

    Conclusions:

    • The observer-based adaptive NN event-triggered control is effective for nonlinear multiagent systems.
    • The approach offers a robust solution for consensus tracking under communication constraints and quantization.
    • The method provides a foundation for future research in distributed control of complex systems.