Add to ORKGThis paper describes the application of model-based predictive control (MPC) techniques to the supervisory flow management in large-scale drinking water networks including a telemetry/telecontrol system. MPC technique is used to generate flow control strategies (set-points for the regulatory controllers) from the sources to the consumer areas to meet future demands, optimizing performance indexes associated to operational goals such as economic cost, network safety volumes and flow control stability. The designed management strategies are applied to a model of a real case study: the drinking water transport network of Barcelona (Spain).Peer Reviewe
In this paper, coordinating technique for the multi-layer model predictive control (MPC) of complex ...
Abstract — This paper addresses the management of drinking water networks (DWNs) regarding a multi-o...
Control of drinking water networks is an arduous task, given their size and the presence of uncertai...
This paper describes the application of model-based predictive control (MPC) techniques to the super...
Abstract: This paper describes the application of model-based predictive control (MPC) techniques to...
Water transport networks (WTNs) are generally used to convey water from production plants or sources...
Transport and supply water networks are two types of systems which have received a significant amoun...
In this chapter, a methodology for the optimal management of combined water supply and navigability/...
An increasing demand for water due to population growth, industrial development and improvement of e...
The coordinated management of regional and urban networks is a challenging real-time control problem...
© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommo...
In this report, MPC strategies have been designed and tested for the global centralized and decentra...
A hierarchical and decentralised model predictive control (DMPC) strategy for drinking water network...
This paper addresses the management of drinking water networks (DWNs) regarding a multi-objective co...
Trabajo presentado al ACC 2010 celebrado en Baltimore (EE.UU.) del 30 de junio al 2 de julio.In thi...
In this paper, coordinating technique for the multi-layer model predictive control (MPC) of complex ...
Abstract — This paper addresses the management of drinking water networks (DWNs) regarding a multi-o...
Control of drinking water networks is an arduous task, given their size and the presence of uncertai...
This paper describes the application of model-based predictive control (MPC) techniques to the super...
Abstract: This paper describes the application of model-based predictive control (MPC) techniques to...
Water transport networks (WTNs) are generally used to convey water from production plants or sources...
Transport and supply water networks are two types of systems which have received a significant amoun...
In this chapter, a methodology for the optimal management of combined water supply and navigability/...
An increasing demand for water due to population growth, industrial development and improvement of e...
The coordinated management of regional and urban networks is a challenging real-time control problem...
© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommo...
In this report, MPC strategies have been designed and tested for the global centralized and decentra...
A hierarchical and decentralised model predictive control (DMPC) strategy for drinking water network...
This paper addresses the management of drinking water networks (DWNs) regarding a multi-objective co...
Trabajo presentado al ACC 2010 celebrado en Baltimore (EE.UU.) del 30 de junio al 2 de julio.In thi...
In this paper, coordinating technique for the multi-layer model predictive control (MPC) of complex ...
Abstract — This paper addresses the management of drinking water networks (DWNs) regarding a multi-o...
Control of drinking water networks is an arduous task, given their size and the presence of uncertai...