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arXiv · 2610.24645

Distributed Real-Time Cooperative Model Predictive Control

Yuning Jiang·Kristína Fedorová·Roland Schwan·Juraj Oravec·Colin N. Jones
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Abstract

This paper presents a novel distributed real-time iterative method for cooperative linear Model Predictive Control (MPC) with polyhedral state and input constraints, implementing a relaxed, recentered logarithmic barrier function. The method transforms centralized MPC problems into a distributed framework using temporal-spatial splitting, facilitating efficient online implementation. To achieve real-time performance, we introduce a distributed convex nonlinear optimization solver with guaranteed global linear convergence. By executing this solver with a fixed number of iterations per sampling time, the resulting near-optimal MPC controller ensures closed-loop stability while maintaining fixed computational complexity. The proposed approach is validated through an illustrative example involving a spring-vehicle-damper system benchmark, demonstrating both its effectiveness and computational efficiency.

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Yuning Jiang, Kristína Fedorová, Roland Schwan, Juraj Oravec, Colin N. Jones. 2026-10-17. Distributed Real-Time Cooperative Model Predictive Control. https://arxiv.org/abs/2610.24645

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