Publication
A distributed predictive control approach for periodic flow-based networks: Application to drinking water systems
Journal Article (2017)
Journal
International Journal of Systems Science
Pages
3106-3117
Volume
48
Number
14
Doc link
http://dx.doi.org/10.1080/00207721.2017.1367051
File
Abstract
This paper proposes a distributed model predictive control (MPC) approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimize the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.
Categories
automation, control theory, optimisation.
Author keywords
flow networks, distributed control, large-scale systems, economic model predictive control
Scientific reference
J.M. Grosso, C. Ocampo-Martínez and V. Puig. A distributed predictive control approach for periodic flow-based networks: Application to drinking water systems. International Journal of Systems Science, 48(14): 3106-3117, 2017.
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