Cooperative Linker for the Distributed Control of the Barcelona Drinking Water Network

Javalera Rincón, V. ORCID:, Cayuela, V.P., Seix, B.M., & Orduña-Cabrera, F. ORCID: (2019). Cooperative Linker for the Distributed Control of the Barcelona Drinking Water Network. In: Proceedings of the 11th International Conference on Agents and Artificial Intelligence (ICAART 2019). pp. 560-567 Porto, Portugal: ICAART. ISBN 978-989-758-350-6 10.5220/0007349105600567.

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This work shows how a Linker agent coordinates a cooperative MAS environment to seek a global optimum. The approach is applied to the Barcelona Drinking Water Network (DWN) administrated by AGBAR where the main problem was to coordinate the control of three different sectors of the network. Each part has a local controller (local agent) to solve the local water demands, but it also has to cooperate with the other agents to satisfy the water demands of the whole network. The cooperative Linker agent implemented, learns by using a Reinforcement Learning algorithm, called PlanningByExploration Behaviour with penalization (Javalera et al., 2019), to converge towards an optimal (or suboptimal) value of each of the variables that connect the local agents. For the training and simulation of the Linker agents real historical data of the Barcelona DWN provided by AGBAR were used, as well as the data to model the distributed topology of the DWN. Moreover, some results of the simulations of this approach in contrast with the results of a centralized Model Predictive Controller are depicted.

Item Type: Book Section
Uncontrolled Keywords: Multi-Agent Systems, Large Scale Systems, Linkage ofModels, Reinforcement Learning, Distributed Control, Water Networks, Large Scale Systems
Research Programs: Advanced Systems Analysis (ASA)
Ecosystems Services and Management (ESM)
Depositing User: Luke Kirwan
Date Deposited: 12 Mar 2019 07:32
Last Modified: 01 Feb 2023 05:00

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