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

被引:20
作者
Wang, Shen [1 ]
Taha, Ahmad F. [1 ]
Abokifa, Ahmed A. [2 ]
机构
[1] Univ Texas San Antonio, Dept Elect & Comp Engn, San Antonio, TX 78249 USA
[2] Univ Illinois, Dept Civil & Mat Engn, Chicago, IL USA
基金
美国国家科学基金会;
关键词
model predictive control; water distribution networks; water quality control; water quality modeling; BOOSTER DISINFECTION; DRINKING-WATER; DISTRIBUTION-SYSTEMS; CHLORINATION; PROPAGATION; OPERATION; TRANSPORT; EVENT; DECAY;
D O I
10.1029/2020WR027771
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页数:27
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