Practical Synchronization of Perturbed Networks of Semi-Passive Systems

We study practical synchronization for heterogeneous networks of nonlinear systems in the presence of bounded perturbations. Under the assumption that the nodes are state semi-passive and the interconnection graph admits a spanning tree, we establish uniform ultimate boundedness of the solutions and, consequently, practical synchronization. That is, we show that the systems’ trajectories approach each other up to a steady-state error. The magnitude of this steady-state error can be made arbitrarily small by increasing a scalar coupling gain. The results are shown to hold under the assumption that (at least) a single “well-located” node in the network enjoys some robustness properties. Our theoretical results are fairly general in regards to the topology and are illustrated in simulation on a case-study of networked mobile robots.

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Published
2024-12-16
DOI
https://doi.org/10.1109/cdc56724.2024.10886798
Citations
1
Primary Topic
Neural Networks Stability and Synchronization
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article
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article

Practical Synchronization of Perturbed Networks of Semi-Passive Systems

Mohamed Maghenem, Elena Panteley, Anes Lazri, Antonio Lorı́a
1 citations
Neural Networks Stability and Synchronization
0.35
article

Practical Synchronization of Perturbed Networks of Semi-Passive Systems

Mohamed Maghenem, Elena Panteley, Anes Lazri, Antonio Lorı́a
article en
1 citations

Abstract

We study practical synchronization for heterogeneous networks of nonlinear systems in the presence of bounded perturbations. Under the assumption that the nodes are state semi-passive and the interconnection graph admits a spanning tree, we establish uniform ultimate boundedness of the solutions and, consequently, practical synchronization. That is, we show that the systems’ trajectories approach each other up to a steady-state error. The magnitude of this steady-state error can be made arbitrarily small by increasing a scalar coupling gain. The results are shown to hold under the assumption that (at least) a single “well-located” node in the network enjoys some robustness properties. Our theoretical results are fairly general in regards to the topology and are illustrated in simulation on a case-study of networked mobile robots.

Institut polytechnique de Grenoble (FR), Centre National de la Recherche Scientifique (FR), Université Paris-Saclay (FR), GIPSA-Lab (FR), Université Grenoble Alpes (FR)
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Neural Networks Stability and Synchronization
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