Publication

Distributed model predictive control using optimality condition decomposition and community detection

Journal Article (2021)

Journal

Journal of Process Control

Pages

54-68

Volume

99

Doc link

https://doi.org/10.1016/j.jprocont.2021.01.007

File

Download the digital copy of the doc pdf document

Authors

Abstract

This work regards the development of a distributed model predictive control strategy for large-scale systems, as centralized implementations often suffer from non-scalability. The decomposition of the overall system into minimally coupled subsystems as well as their coordination are based on optimality condition decomposition (OCD) and community detection. The OCD approach allows to solve the associated control subproblems in parallel in an iterative manner until the required degree of accuracy is attained. The proposed strategy is tested on two different systems, the quadruple-tank system and the Barcelona drinking water network, which allow to highlight the effectiveness of the approach.

Categories

optimisation, predictive control.

Author keywords

model predictive control, distributed control systems, water network

Scientific reference

P. Segovia, V. Puig, E. Duviella and L. Etienne. Distributed model predictive control using optimality condition decomposition and community detection. Journal of Process Control, 99: 54-68, 2021.