A Parametric Multi-Convex Splitting Technique with Application to Real-Time NMPC
Optimization and Control
2014-07-22 v1
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.
Cite
@article{arxiv.1407.5427,
title = {A Parametric Multi-Convex Splitting Technique with Application to Real-Time NMPC},
author = {Jean-Hubert Hours and Colin N. Jones},
journal= {arXiv preprint arXiv:1407.5427},
year = {2014}
}
Comments
To appear in Proceedings of the 53rd IEEE Conference on Decision and Control 2014