Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.704839
Title: Model predictive control of water quality in drinking water distribution systems considering disinfection by-products
Author: Xie, Mingyu
ISNI:       0000 0004 6057 3468
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2017
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Abstract:
The shortage in water resources have been observed all over the world. However, the safety of drinking water has been given much attention by scientists because the disinfection will react with organic matters in drinking water to generate disinfection by-products (DBPs) which are considered as the cancerigenic matters. Although much research has been carried out on the water quality control problem in DWDS, the water quality model considered is linear with only chlorine dynamics. Compared to the linear water quality model, the nonlinear water quality model considers the interaction between chlorine and DBPs dynamics. The thesis proposes a nonlinear model predictive controller which utilises the newly derived nonlinear water quality model as a control alternative for controlling water quality. EPANET and EPANET-MSN are simulators utilised for modelling in the developed nonlinear MPC controller. Uncertainty is not considered in these simulators. This thesis proposes the bounded PPM in a form of multi-input multi-output to robustly bound parameters of chlorine and DBPs jointly and to robustly predict water quality control outputs for quality control purpose. The methodologies and algorithms developed in this thesis are verified by applying extended case studies to the example DWDS. The simulation results are presented and critically analysed.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.704839  DOI: Not available
Keywords: TD Environmental technology. Sanitary engineering ; TK Electrical engineering. Electronics Nuclear engineering
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