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PreprintCC BY 4.0arXiv

Asynchronous Sensitivity-Based Distributed NMPC

  • Maximilian Pierer von Esch
  • Andres Völz
  • Knut Graichen
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Abstract

This paper presents a cooperative distributed model predictive control (MPC) scheme for nonlinear continuous-time systems. The centralized optimal control problem is solved asynchronously via a fixed number of sensitivity-based distributed programming (SBDP) iterations. The proposed scheme requires only neighbor-to-neighbor communication and no synchronization between agents during optimization. Under nominal MPC stability and bounded information delay, local exponential stability is established for a sufficiently large number of per-agent SBDP iterations. Numerical and hardware-in-the-loop results on both Ethernet and Wi-Fi demonstrate the benefits of an asynchronous execution, reducing execution times by over 60% while maintaining comparable closed loop performance.

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Cite

BibTeXRIS
BibTeX
@misc{esch2026asynchronous,
  title = {{Asynchronous Sensitivity-Based Distributed NMPC}},
  author = {Maximilian Pierer von Esch and Andres Völz and Knut Graichen},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2607.03412},
  eprint = {2607.03412},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2607.03412},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Asynchronous Sensitivity-Based Distributed NMPC
AU  - Maximilian Pierer von Esch
AU  - Andres Völz
AU  - Knut Graichen
PY  - 2026
DA  - 2026/10/26
PB  - arXiv
DO  - 10.48550/arxiv.2607.03412
UR  - https://arxiv.org/abs/2607.03412
AB  - This paper presents a cooperative distributed model predictive control (MPC) scheme for nonlinear continuous-time systems. The centralized optimal control problem is solved asynchronously via a fixed number of sensitivity-based distributed programming (SBDP) iterations. The proposed scheme requires only neighbor-to-neighbor communication and no synchronization between agents during optimization. Under nominal MPC stability and bounded information delay, local exponential stability is established for a sufficiently large number of per-agent SBDP iterations. Numerical and hardware-in-the-loop results on both Ethernet and Wi-Fi demonstrate the benefits of an asynchronous execution, reducing execution times by over 60% while maintaining comparable closed loop performance.
ER  -