Singularly Perturbed Hybrid Systems for Analysis of Networks With Frequently Switching Graphs

For a class of hybrid systems, where jumps occur frequently, we analyze the stability of system trajectories in view of singularly perturbed dynamics. The specific model we consider comprises an interconnection of two hybrid subsystems, a timer which triggers the jumps, and some discrete variables to determine the index of the jump maps. The flow equations of these variables are singularly perturbed differential equations and, in particular, a smaller value of the singular perturbation parameter leads to an increase in the frequency of the jump instants. For the limiting value of this parameter, we consider a decomposition that comprises a quasi-steady-state system modeled by a differential equation without any jumps and a boundary-layer system described by purely discrete dynamics. Under appropriate assumptions on the quasi-steady-state system and the boundary-layer system, we derive results showing practical stability of a compact attractor when the jumps occur sufficiently often. As an application of our results, we discuss the control design problem in a network of second-order continuous-time coupled oscillators, where each agent communicates the information about its position to some of its neighbors at discrete times. Using the results developed in this article, we show that if the union of the communication graphs being used for information exchange between agents is connected, then the oscillators achieve practical consensus.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2024-12-26
DOI
https://doi.org/10.1109/tac.2024.3523242
Citations
1
Primary Topic
Advanced Research in Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
0.33

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article

Singularly Perturbed Hybrid Systems for Analysis of Networks With Frequently Switching Graphs

Andrew R. Teel, Aneel Tanwani, Hyungbo Shim
1 citations
IEEE Transactions on Automatic Control
Advanced Research in Systems and Signal Processing
0.33
article

Singularly Perturbed Hybrid Systems for Analysis of Networks With Frequently Switching Graphs

Andrew R. Teel, Aneel Tanwani, Hyungbo Shim
article en
1 citations

Abstract

For a class of hybrid systems, where jumps occur frequently, we analyze the stability of system trajectories in view of singularly perturbed dynamics. The specific model we consider comprises an interconnection of two hybrid subsystems, a timer which triggers the jumps, and some discrete variables to determine the index of the jump maps. The flow equations of these variables are singularly perturbed differential equations and, in particular, a smaller value of the singular perturbation parameter leads to an increase in the frequency of the jump instants. For the limiting value of this parameter, we consider a decomposition that comprises a quasi-steady-state system modeled by a differential equation without any jumps and a boundary-layer system described by purely discrete dynamics. Under appropriate assumptions on the quasi-steady-state system and the boundary-layer system, we derive results showing practical stability of a compact attractor when the jumps occur sufficiently often. As an application of our results, we discuss the control design problem in a network of second-order continuous-time coupled oscillators, where each agent communicates the information about its position to some of its neighbors at discrete times. Using the results developed in this article, we show that if the union of the communication graphs being used for information exchange between agents is connected, then the oscillators achieve practical consensus.

IEEE Transactions on Automatic ControlVol. 70(7)
Centre National de la Recherche Scientifique (FR), Seoul National University (KR), University of California, Santa Barbara (US), Université Fédérale de Toulouse Midi-Pyrénées (FR), Laboratoire d'Analyse et d'Architecture des Systèmes (FR), Toulouse Mathematics Institute (FR)
National Research Foundation of Korea, Air Force Office of Scientific Research
Climate action
Openalex Percentile: Top 38%
Advanced Research in Systems and Signal Processing
0.33
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