Abstract
This thesis aims to develop a predictive control for irrigation canals to improve the management of water resources. Water is necessary for life and it is a scarce good that we need for drinking, in the agriculture, etc. At the same time, it can constitute a serious threat in particular areas due to the difficulty to grow foods by the increasing of prolonged droughts. The agriculture holds an important part of the food chain and the water resources for agriculture are important, the problem is the water transport systems present low efficiencies in practice. The yield agriculture has to be optimized, because the goal of an operational water manager is to deliver the water to the irrigation sites accurately and efficiently. To improve the efficiency of the water transport systems is necessary to invest in automating the operation of irrigation canals. In order to fulfill these objectives, we define an overall control diagrams scheme in chapter 5 which splits the management of the canal control in different blocks. The management of a canal start from setting the demand delivery accurately taking into account the crops necessities during an irrigation cycle and establishing the gate trajectories for controlling the canal in each time step. In an ideal case, the system would be controlled but some factors which could deviated the desired state for the canal from the real canal state, as for instance, a disturbance introduced into the canal. In that circumstances, it would be necessary to introduce in our overall control diagram, other algorithms which could aid the watermaster to restore the desired state of the canal. These algorithms, developed and tested for us, are the CSI and GoRoSoBo algorithms. The first one defines a powerful tool in the management of a canal. The Watermaster establishes the gates positions and fixes the desired water level at checkpoints to fulfill a scheduled demand. In that sense, when someone introduce a disturbance into the canal perturbs the water level at checkpoints, so the scheduled deliveries cannot fulfilled by the watermaster. In such case, the water level measurements at these checkpoints could be sent to the CSI algorithms which calculates the real extracted flow and the current canal state along the canal, that is, the water level and velocity in all cross-sections of the canal. This task is performed by the CSI algorithm which has been designed in this thesis and tested in numerous numerical examples (chapter 7) and experimentally in a laboratory canal of the Technical University of Catalonia (chapter 8). The last one is the essential tool in the management of a canal, that is, a control algorithm operating in real-time. The GoRoSoBo algorithm (Gomez, Rodellar, Soler, Bonet) is a feedback control algorithm which calculates the optimum gates trajectories for a predictive horizon taking into account the current canal state obtained by CSI as well as the scheduled demands and the previous gate trajectories. GoRoSoBo has been designed in this thesis and tested in several numerical examples (chapter 10) as the Test-Case proposed by the ASCE Task Committee on Canal Automation Algorithms (chapter 11). In that sense, we propose a centralized control performance to manage the canal control. In addition to these two main contributions, many other smaller developments, minor results and practical recommendations for irrigation canal automation are presented throughout this thesis.
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