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Distributed Real-Time MPC with Convergence Guarantees

US & West · 20 Oct

A distributed iterative method is presented for cooperative linear MPC with polyhedral state and input constraints, using a logarithmic barrier function. The centralized problem is turned into a distributed scheme with a convex nonlinear solver guaranteeing global linear convergence. A fixed iteration count per sampling step ensures closed-loop stability at constant computational cost.

Why it matters

Real-time distributed solvers matter for controlling systems that cannot be handled by a single centralized optimizer.

Original headline: Distributed Real-Time Cooperative Model Predictive Control

Read the original: arXiv — Systems and Control (eess.SY)

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