A master thesis from Aalborg University
Iterative Learning Pressure Control and Leakage Localization in Water Network Distribution
Author(s)
Term
4. term
Education
Publication year
2022
Submitted on
2022-06-02
Pages
91 pages
Abstract
The purpose of this project is to test if it is possible to implement an Iterative Learning-based Control (ILC) in the AAU Smart Water Infrastructure Laboratory and what effect it has on such a system. By taking this into account, the plan was to try and implement ILC and include a leakage detection method in the water network. This specific implementation was plausible due to consumers using the water repeatedly, thus allowing for ILC to be used. In this report, specific requirements were made to allow the testing of such control. Later in the report, modeling for the water distribution network was made, which includes static and dynamic models. Then, after introducing ILC, multiple tests were conducted for both simulations and in an actual lab. To detect the leakages in the network, pressure residuals are generated from the difference between the dynamic model measurements and estimated values from the static model to compare it with a threshold that identifies the leak. In conclusion, it is plausible for ILC based controller to be implemented in the water lab and can be expanded even further in the future.
Keywords
ILC ; Iterative Learning Control ; Water Distriubtion Network ; AAU Lab ; Water Lab ; Leakage Detection ; Dynamic Model ; Static Model ; Artis ; Danas ; Ibrahim ; Leakage Localization ; Master Thesis ; SWIL ; Simulation ; MATLAB ; Modeling
Documents
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