Non-centralized predictive control for drinking-water supply systems

Book Chapter (2017)

Book Title

Real-Time Monitoring and Operational Control of Drinking-Water Systems








Advances in Industrial Control

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Model-based predictive control (MPC) has been proved to be one of the most widely accepted advanced control technique for the operational control of water systems. Nevertheless, the main hurdle for MPC control, as any other control technique, when applied to large-scale networks in a centralised way, is the nonscalability. The reason is that a huge control model is required along with the need of being rebuilt on every change in the system configuration as, for example, when some part of the network should be stopped because of maintenance actions or malfunctions. A way of circumventing these issues might be by looking into decentralised MPC (DMPC) or distributed MPC techniques, where networked local MPC controllers are in charge of controlling each one a part of the entire system. The success of centralised MPC (CMPC) drives now a new interest in this old area of distributed control, becoming DMPC one of the hottest topics in control during the early 21st century. This chapter presents and discusses the application in simulation of a hierarchical like DMPC approach to the Barcelona drinking water network (DWN). The aim of DMPC is to reduce the computational burden and to increase scalability and modularity with respect to the centralised counterpart, but still maintaining a convenient level of suboptimality with respect to the desired control objectives. Moreover, the advantage of hierarchical-like DMPC approach is the simplicity of its implementation given the absence of negotiations among controllers, which allows for a simple implementation from the networking viewpoint.


automation, control theory, optimisation.

Author keywords

non-centralized control, predictive control, flow networks

Scientific reference

J.M. Grosso, C. Ocampo-Martínez and V. Puig. Non-centralized predictive control for drinking-water supply systems. In Real-Time Monitoring and Operational Control of Drinking-Water Systems, 341-360. Springer, 2017.