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December 4, 2025International Journal of Adaptive Control and Signal Processing

Quantized Iterative Learning Control for Consensus of Nonlinear Impulsive Multi‐Agent Systems With Inter‐Channel Encoding‐Decoding Mechanisms and Packet Dropouts

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Authors

HZHongjin ZhangJWJinrong WANGDSDong Shen

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Overview

This approach demonstrates consensus in multi-agent systems with packet dropouts, indicating improved stability under bandwidth constraints.

Key Points

  • Consensus is achieved in multi-agent systems with packet dropouts, enhancing system reliability.
  • The key metric involves reductions in tracking error across independent channels in the network.
  • This is a novel distributed control algorithm leveraging quantized signals for effective communication.
  • Findings support further exploration of learning control strategies in complex multi-agent scenarios.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/6930dc8aea1aef094cca28cbhttps://doi.org/10.1002/acs.70017
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Adaptive Impulsive Consensus of Nonlinear Multiagent Systems With Limited Bandwidth Under Uncertain Deception Attacks2024 · 6 citations
  2. 2Consensus for discrete-time multi-agent systems without the precise model of packet dropouts2026
  3. 3Online Value Iteration for Unknown Nonlinear Multiagent Systems: A Model-Decoupled Encoding–Decoding Mechanism2026 · 1 citations
  4. 4Limited Impulsive Control of Time-Delay Multiagent Systems With Packet Loss and Parameter Mismatch2025 · 3 citations
  5. 5Optimisation-Based Iterative Learning Control for Distributed Consensus Tracking2024 · 1 citations