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Prescribed-performance consensus control for nonlinear MASs: a privacy preservation strategy.

Kairui Chen1, Chengzhen Yu1, Zhi Liu2

  • 1School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, Guangdong, China.

ISA Transactions
|November 14, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel control strategy for nonlinear multi-agent systems, ensuring data privacy and fast, accurate consensus. The adaptive predefined-time prescribed performance control enhances system security and performance.

Keywords:
Fuzzy logic systemsMulti-agent systemsPrescribed performance constraintPrescribed-time stabilityPrivacy preservation

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Area of Science:

  • Control Theory
  • Networked Systems
  • Cybersecurity

Background:

  • Nonlinear multi-agent systems face challenges in achieving consensus while maintaining data privacy.
  • Existing control strategies may not adequately address both performance and security requirements simultaneously.
  • The need for robust and efficient consensus protocols in distributed systems is critical.

Purpose of the Study:

  • To develop an adaptive predefined-time prescribed performance control strategy for nonlinear multi-agent systems.
  • To integrate a privacy-preservation mechanism to protect data during transmission.
  • To ensure rapid and accurate consensus among agents while guaranteeing data confidentiality.

Main Methods:

  • A privacy preservation method using adjustable mask factors for unique node encryption.
  • A prescribed performance mechanism to constrain tracking errors using masked data.
  • An adaptive predefined-time filter and filtering error compensation technique.
  • Development of a predefined-time prescribed performance consensus protocol.

Main Results:

  • The proposed strategy effectively protects transmitting data within a user-defined time.
  • The privacy preservation method enhances data security through unique encryption per node.
  • The prescribed performance mechanism successfully constrains tracking errors.
  • Simulations demonstrate the efficacy of the predefined-time prescribed performance consensus protocol.

Conclusions:

  • The adaptive predefined-time prescribed performance control strategy achieves privacy-preserving consensus in nonlinear multi-agent systems.
  • The integration of privacy preservation and prescribed performance control offers a robust solution for secure networked systems.
  • The proposed method enhances both the security and the performance of multi-agent systems.