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Event-Based Integral Sliding-Mode Consensus Control for Networked Multiagent Systems With State Quantization.

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    This study introduces a new controller for networked multiagent systems (MASs) using event-triggered integral sliding-mode control (SMC) with quantization. This approach efficiently manages limited bandwidth while ensuring system stability and consensus.

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    Area of Science:

    • Control Engineering
    • Networked Systems
    • Multiagent Systems

    Background:

    • Networked multiagent systems (MASs) face challenges with limited bandwidth and interferences.
    • Traditional control methods can be communication-intensive, straining network resources.
    • Integral sliding-mode control (SMC) is effective for disturbance rejection but requires efficient implementation in networked settings.

    Purpose of the Study:

    • To design a quantization-based event-triggered integral sliding-mode controller for MASs.
    • To address interferences and limited network bandwidth in MASs.
    • To ensure asymptotic average consensus in networked MASs.

    Main Methods:

    • Design of an integral sliding manifold (ISM) to handle disturbances.
    • Development of an event-triggered mechanism (ETM) with an exponential decay rate for resource conservation.
    • Integration of a uniform quantizer to reduce data transmission load.
    • Construction of a quantized ISM using triggered state signals.
    • Development of an event-triggered integral sliding-mode controller incorporating quantization technology.

    Main Results:

    • The proposed controller ensures asymptotic average consensus for networked MASs.
    • The event-triggered mechanism (ETM) demonstrates viability by ensuring a lower positive bound for network agents, preventing Zeno behavior.
    • Simulation examples confirm the effectiveness of the quantization feedback-based event-triggered SMC methodology.

    Conclusions:

    • The developed controller effectively manages limited network bandwidth in MASs through quantization and event-triggering.
    • The approach guarantees system stability and achieves average consensus.
    • The methodology is validated for its efficacy in practical networked control scenarios.