Economic Model Predictive Control of a Wastewater Treatment Plant using Neural and Fuzzy models

被引：5

作者：

Revollar, Silvana ^{[1
]}

Alvarez, Hernan ^{[2
]}

Lamanna, Rosalba ^{[3
]}

Vega, Pastora ^{[1
]}

Goldar, Alejandro ^{[3
]}

机构：

[1] Univ Salamanca, Dept Informat & Automat, E-37008 Salamanca, Spain

[2] Univ Nacl Colombia, Escuela Proc & Energia, Medellin, Colombia

[3] Univ Simon Bolivar, Dept Proc & Sistemas, Caracas 89000, Venezuela

来源：

28TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING | 2018年 / 43卷

关键词：

Economic model predictive control; neural networks; fuzzy systems;

D O I：

10.1016/B978-0-444-64235-6.50215-1

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

To improve efficiency in wastewater treatment plants, suitable optimization and control strategies for the activated sludge process are imperative. Therefore, adequate models for estimation of the critical variables are also vital. In this work, neural networks and fuzzy models are identified from data collected from a standard benchmark simulation platform (BSM1) used to represent the activated sludge process. These models are embedded in an economic predictive controller designed to regulate critical variables to ensure the desired effluent quality with the minimum energy consumption.

引用

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页码：1237 / 1242

页数：6

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