Mixed-Integer Programming Techniques in Distributed MPC Problems

Ionela Prodan 1 Florin Stoican 1 Sorin Olaru 1 Cristina Stoica 1 Silviu-Iulian Niculescu 2, 3, 4
1 E3S - Supélec Sciences des Systèmes [Gif-sur-Yvette]
2 DISCO - Dynamical Interconnected Systems in COmplex Environments
L2S - Laboratoire des signaux et systèmes, Inria Saclay - Ile de France, SUPELEC, CNRS - Centre National de la Recherche Scientifique : UMR8506
3 Division Systèmes - L2S
L2S - Laboratoire des signaux et systèmes : 1289
4 L2S - Laboratoire des signaux et systèmes
Abstract : This chapter proposes a distributed approach for the resolution of a multi-agent problem under collision and obstacle avoidance conditions. Using hyperplane arrangements and mixed integer programming, we provide an efficient description of the feasible region verifying the avoidance constraints. We exploit geometric properties of hyperplane arrangements and adapt this description to the distributed scheme in order to provide an efficient Model Predictive Control (MPC) solution. Furthermore, we prove constraint validation for a hierarchical ordering of the agents.
Type de document :
Chapitre d'ouvrage
Maestre, José M. and Negenborn, Rudy R. Distributed Model Predictive Control Made Easy, Springer, pp.273-288, 2013, 〈10.1007/978-94-007-7006-5_17〉
Liste complète des métadonnées
https://hal.inria.fr/hal-00826633
Contributeur : Josiane Dartron <>
Soumis le : mardi 28 mai 2013 - 09:10:33
Dernière modification le : mardi 18 septembre 2018 - 01:01:59

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Ionela Prodan, Florin Stoican, Sorin Olaru, Cristina Stoica, Silviu-Iulian Niculescu. Mixed-Integer Programming Techniques in Distributed MPC Problems. Maestre, José M. and Negenborn, Rudy R. Distributed Model Predictive Control Made Easy, Springer, pp.273-288, 2013, 〈10.1007/978-94-007-7006-5_17〉. 〈hal-00826633〉

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