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arXiv · 2607.03412

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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Maximilian Pierer von Esch, Andres Völz, Knut Graichen. 2026-07-03. Asynchronous Sensitivity-Based Distributed NMPC. https://arxiv.org/abs/2607.03412

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