Direct model predictive control - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Direct model predictive control

Abstract

Due to simplicity and convenience, Model Predictive Control, which consists in optimizing future decisions based on a pessimistic deterministic forecast of the random processes, is one of the main tools for stochastic control. Yet, it suffers from a large computation time, unless the tactical horizon (i.e. the number of future time steps included in the optimization) is strongly reduced, and lack of real stochasticity handling. We here propose a combination between Model Predictive Control and Direct Policy Search.
Fichier principal
Vignette du fichier
dpsandmpc.pdf (177.05 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-00958192 , version 1 (11-03-2014)

Identifiers

  • HAL Id : hal-00958192 , version 1

Cite

Jean-Joseph Christophe, Jérémie Decock, Olivier Teytaud. Direct model predictive control. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Apr 2014, Bruges, Belgium. ⟨hal-00958192⟩
350 View
327 Download

Share

Gmail Mastodon Facebook X LinkedIn More