# Incremental Proximal Multi-Forecast Model Predictive Control

arXiv: https://arxiv.org/abs/2111.14728 · HTML: https://mlsanity.com/paper/2111.14728/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Nov 2021.

## Built on by (most cited first, 2 of 2)

- [Stochastic Optimal Control via Measure Relaxations](https://mlsanity.com/paper/2508.00886/) (2025)
- [Accounting for Optimal Control in the Sizing of Isolated Hybrid Renewable Energy Systems Using Imitation Learning](https://mlsanity.com/paper/2601.03679/) (2026)

## Abstract (arXiv)

Multi-forecast model predictive control (MF-MPC) is a control policy that creates a plan of actions over a horizon for each of a given set of forecasted scenarios or contingencies, with the constraint that the first action in all plans be the same. In this note we show how these coupled plans can be found by solving a sequence of single plans, using an incremental proximal method. We refer to this policy as incremental proximal model predictive control (IP-MPC). We have observed that even when the iterations in IP-MPC are not carried out to convergence, we obtain a policy that achieves much of the improvement of MF-MPC over single-forecast model predictive control (MPC).