Distributed model predictive control using optimality condition decomposition and community detection

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 overall system into minimally coupled subsystems well their coordination are based on optimality condition (OCD) and community detection. OCD approach allows to solve associated subproblems in parallel an iterative manner until required degree accuracy is attained. proposed tested two different quadruple-tank Barcelona drinking water network, which allow highlight effectiveness approach.