A Parametric Multi-Convex Splitting Technique with Application to Real-Time NMPC

2014/07/21 by Jean-Hubert Hours, Hours, Jean-Hubert, Colin N. Jones +1 · 1 citation
Engineering · Mathematics · Medicine · #Advanced Control Systems Optimization #Cardiovascular Function and Risk Factors #FOS: Mathematics #Optimization and Control (math.OC) #Pancreatic function and diabetes #math.OC

paper · pdf · doi:10.48550/arxiv.1407.5427

To appear in Proceedings of the 53rd IEEE Conference on Decision and Control 2014

arxiv created 2014/07/21 · openalex publication_date 2014/07/21 · arxiv updated 2014/07/22 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/28

Abstract

A novel splitting scheme to solve parametric multiconvex programs is presented. It consists of a fixed number of proximal alternating minimisations and a dual update per time step, which makes it attractive in a real-time Nonlinear Model Predictive Control (NMPC) framework and for distributed computing environments. Assuming that the parametric program is semi-algebraic and that its KKT points are strongly regular, a contraction estimate is derived and it is proven that the sub-optimality error remains stable if two key parameters are tuned properly. Efficacy of the method is demonstrated by solving a bilinear NMPC problem to control a DC motor.

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