Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
November 11, 2025ActuatorsOpen Access

Adaptive Fuzzy Leader-Following Consensus Quantized Control for High-Order Nonlinear Multi-Agent Systems

View Full Paper
Ask AI
Bookmark
Share

Authors

YLYifan LiuMMMin MaTWTong Wang

Discussion

Loading...

Member takes

Overview

Control strategy achieves consensus in multi-agent systems, indicating effective tracking despite quantized inputs.

Key Points

  • Control strategy ensures consensus tracking in multi-agent systems, enhancing team performance.
  • Numerical simulation demonstrates effectiveness, showing significant improvements in coordination.
  • Utilization of states information from subsystems and neighbors supports robust control implementation.
  • Potential benefits highlight the need for further exploration of quantized input influence on dynamics.

Cite This Study

Liu et al. (2025) studied this question.

synapsesocial.com/papers/69252e90c0ce034ddc355f08https://doi.org/10.3390/act14110552
View Full Paper
Ask AI
Bookmark
Share

Also Consider

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

  1. 1Distributed Output-Feedback Asymptotic Consensus Tracking for High-Order Multiagent Systems With Quantized Input2024 · 2 citations
  2. 2Nonsingular adaptive finite-time consensus control for uncertain nonlinear multi-agent systems with input quantization2024 · 2 citations
  3. 3Quantized output‐feedback event‐triggered distributed control of switched fractional multi‐agent systems subject to input nonlinearities and consensus error constraints2024 · 1 citations
  4. 4Quantization-Based Adaptive Fuzzy Consensus for Multiagent Systems Under Sensor Deception Attacks: A Novel Compensation Mechanism2024 · 3 citations
  5. 5Quantised adaptive consensus control of heterogeneous nonlinear multi-agent systems under external disturbance2024 · 4 citations