English

How Effective is Model Predictive Control in Real-Time Water Quality Regulation? State-Space Modeling and Scalable Control

Optimization and Control 2021-06-09 v2 Systems and Control Systems and Control

Abstract

Real-time water quality control (WQC) in water distribution networks (WDN), the problem of regulating disinfectant levels, is challenging due to lack of (i) a proper control-oriented modeling considering complicated components (junctions, reservoirs, tanks, pipes, pumps, and valves) for water quality modeling in WDN and (ii) a corresponding scalable control algorithm that performs real-time water quality regulation. In this paper, we solve the WQC problem by (a) proposing a novel state-space representation of the WQC problem that provides an explicit relationship between inputs (chlorine dosage at booster stations) and states/outputs (chlorine concentrations in the entire network) and (b) designing a highly scalable model predictive control (MPC) algorithm that showcases fast response time and resilience against some sources of uncertainty.

Keywords

Cite

@article{arxiv.2009.01298,
  title  = {How Effective is Model Predictive Control in Real-Time Water Quality Regulation? State-Space Modeling and Scalable Control},
  author = {Shen Wang and Ahmad F. Taha and Ahmed A. Abokifa},
  journal= {arXiv preprint arXiv:2009.01298},
  year   = {2021}
}