Cooperative Behaviors of Thermodynamic Kuramoto Model Under External Fields

Article Automation & Control Systems

Consensus Analysis of Connected Vehicle System with Stochastic Multiplicative Noises

Ziyuan Li et al.

Summary: This paper researches the consensus of autonomous connected vehicle system (CVS) under stochastic multiplicative noise, proposing two noise resistance methods: parameter restriction method and interaction network-based method. The former restricts control parameters to meet requirements, while the latter ensures system convergence by introducing a virtual system. The effectiveness of these methods is verified through simulations.

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS (2021)

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Article Automation & Control Systems

A Novel Intermediate Estimator Based Secure Consensus Control for Multi-agent Systems with Application to Networked Multi-axis Motion Synchronization

Jun-Wei Zhu et al.

Summary: This paper investigates the secure consensus control problem of multi-agent systems under DoS attacks, proposing a resilient intermediate estimator-based attack tolerant control strategy. By leveraging hardware redundancies, both estimators and control protocols can be reconstructed online according to different attack scenarios. Experimental results of a networked multi-axis motion control system validate the effectiveness of the proposed method.

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS (2021)

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Article Computer Science, Artificial Intelligence

The effect of noise on the synchronization dynamics of the Kuramoto model on a large human connectome graph

Geza Odor et al.

Summary: This study extends the investigation of the Kuramoto model with additive Gaussian noise on the KKI-18 large human connectome graph, and numerically determines the dynamical behavior of the model in an assumed homeostatic state. The desynchronization duration distributions exhibit power-law tails with exponent overlapping in vivo human brain activity experiments, and scaling results remain valid with a transformation of ultra-slow eigenfrequencies to Gaussian distribution. Comparisons with results on a regular cube with 106 nodes show that internal frequencies can cause frustrated synchronization scaling in an extended coupling space.

NEUROCOMPUTING (2021)

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Article Automation & Control Systems