Adaptive Resilient Flexible-Containment Control for Fully Heterogeneous MASs Subject to DoS Attacks and Asynchronous Semi-Markov Chains

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Summary

This summary is machine-generated.

This study introduces adaptive resilient control for multiagent systems facing communication issues and varying dynamics. The new method ensures flexible output containment despite uncertainties and attacks.

Area Of Science

  • Control Systems Engineering
  • Networked Systems
  • Artificial Intelligence

Background

  • Multiagent systems (MASs) face challenges with heterogeneity, switching topologies, and denial-of-service (DoS) attacks.
  • Existing containment control methods often struggle with fully heterogeneous MASs and uncertain system dynamics.

Purpose Of The Study

  • To develop an adaptive resilient flexible output containment (FOC) control strategy for semi-Markov jump fully heterogeneous multiagent systems (FHMASs).
  • To address challenges posed by random switching topologies, DoS attacks, and leader heterogeneity.

Main Methods

  • Employed multiple asynchronous semi-Markov chains to model parameter variations and topology switching with uncertain transition rates (TRs).
  • Developed a novel adaptive observer-based FOC control framework with adaptive gains for state observation.
  • Designed a dynamic output feedback controller, decoupling containment coefficients from the Laplacian matrix.
  • Utilized linear matrix inequalities (LMIs) to derive gain matrices under uncertain TRs.

Main Results

  • Adaptive observers successfully estimated leader states despite unknown global topology and TRs, while resisting DoS attacks and topology switching.
  • The dynamic output feedback controller achieved flexible output containment (FOC).
  • Containment coefficients can be flexibly predefined, enhancing adaptability.
  • LMIs provided a systematic way to obtain controller and estimator gains.

Conclusions

  • The proposed adaptive resilient FOC control framework is effective for FHMASs under complex conditions.
  • The method offers enhanced robustness against uncertainties and external attacks.
  • The flexible FOC design broadens applicability in real-world scenarios.

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