Networked cooperation-based distributed model predictive control using Laguerre functions for large-scale systems

Kamel Menighed (1) , Ahmed Chemori (2) , Boumedyen Boussaid (3) , Joseph Juien Yamé (4)

1 Université 20 Août 1955 Skikda
2 DEXTER - Robotique médicale et mécanismes parallèles
3 ENIG - Ecole Nationale d'Ingénieurs de Gabès
4 CRAN - Centre de Recherche en Automatique de Nancy

This paper proposes a novel cooperative distributed control system architecture based on unsupervised and independent Model Predictive Control (MPC) using discrete-time Laguerre functions to improve the performance of the whole system. In this distributed framework, local MPCs algorithms might exchange and require information from other sub-controllers via the communication network to achieve their task in a cooperative way. In order to reduce the computational burden in the local rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are used to approximate the predicted control trajectory. Simulation results show that the proposed architecture could guarantee satisfactory global performance even under strong interactions among the subsystems.

Mots clés: Large-scale interconnected systems; Distributed model predictive control; Laguerre functions

Domaines: Automatique / Robotique

Kamel Menighed, Ahmed Chemori, Boumedyen Boussaid, Joseph Juien Yamé. Networked cooperation-based distributed model predictive control using Laguerre functions for large-scale systems. 4th International Conference on Electrical Engineering and Control Applications, ICEECA 2019, Dec 2019, Constantine, Algeria. ⟨10.1007/978-981-15-6403-1_9⟩. ⟨hal-02420187⟩