Neural Network Adaptive Control of Dissolved Oxygen for an Activated Sludge process

2019 ◽  
Author(s):  
Nissrine Drioui ◽  
El Houssine el Mazoudi ◽  
Jamila El Alami
Keyword(s):  
Neural Network ◽  
Adaptive Control ◽  
Dissolved Oxygen ◽  
Activated Sludge ◽  
Activated Sludge Process

scholarly journals Auto-Control Technique Using Gradient Method Based on Radial Basis Function Neural Networks to Control of an Activated Sludge Process of Wastewater Treatment

2020 ◽  
Vol 53 (5) ◽  
pp. 671-679
Author(s):  
Abdallah Lemita ◽  
Sebti Boulahbel ◽  
Sami Kahla ◽  
Moussa Sedraoui
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Wastewater Treatment ◽  
Dissolved Oxygen ◽  
Activated Sludge ◽  
Control Strategy ◽  
Rbf Neural Network ◽  
Activated Sludge Process ◽  
Treatment Processes ◽  
Do Concentration

Dissolved oxygen (DO) concentration is a key variable in the activated sludge wastewater treatment processes. In this paper, an auto control strategy based on Euler method and gradient method with radial basis function (RBF) neural networks (NNs) is proposed to solve the DO concentration control problem in an activated sludge process of wastewater treatment. The control purpose is to maintain the dissolved oxygen concentration in the aerated tank for having the substrate concentration within the standard limits established by legislation of wastewater treatment. For that reason, a new proposed control strategy based on gradient descent method and RBF neural network has been used. Compared with RBF neural network PI control, the obtained results show the effectiveness in terms of both transient and steady performances of proposed control method for dissolved oxygen control in the activated sludge wastewater treatment processes.

Operational Determination of the Activated Sludge Process Using Neural Networks

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2461-2464 ◽  
Author(s):  
R. D. Tyagi ◽  
Y. G. Du
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Steady State ◽  
Activated Sludge ◽  
Feedforward Neural Network ◽  
Training Data ◽  
Activated Sludge Process

A steady-statemathematical model of an activated sludgeprocess with a secondary settler was developed. With a limited number of training data samples obtained from the simulation at steady state, a feedforward neural network was established which exhibits an excellent capability for the operational prediction and determination.

Determination of Operating Conditions in Activated Sludge Process Using Fuzzy Neural Network and Genetic Algorithm

2001 ◽  
Vol 34 (8) ◽  
pp. 1033-1039 ◽  
Author(s):  
HIROKI YOSHIKAWA ◽  
TAIZO HANAI ◽  
SHUTA TOMIDA ◽  
HIROYUKI HONDA ◽  
TAKESHI KOBAYASHI
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Activated Sludge ◽  
Fuzzy Neural Network ◽  
Operating Conditions ◽  
Activated Sludge Process ◽  
Fuzzy Neural
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