# A Distributed Active Set Method for Model Predictive Control

arXiv: https://arxiv.org/abs/2103.12681 · HTML: https://mlsanity.com/paper/2103.12681/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Mar 2021.

## Built on by (most cited first, 1 of 1)

- [Learning-enabled Acceleration of Scenario-based Model Predictive Control](https://mlsanity.com/paper/2607.12775/) (2026)

## Abstract (arXiv)

This paper presents a novel distributed active set method for model predictive control of linear systems. The method combines a primal active set strategy with a decentralized conjugate gradient method to solve convex quadratic programs. An advantage of the proposed method compared to existing distributed model predictive algorithms is the primal feasibility of the iterates. Numerical results show that the proposed method can compete with the alternating direction method of multipliers in terms of communication requirements for a chain of masses example.