scholarly journals Intelligent Control/Operational Strategies in WWTPs through an Integrated Q-Learning Algorithm with ASM2d-Guided Reward

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 927 ◽  
Author(s):  
Jiwei Pang ◽  
Shanshan Yang ◽  
Lei He ◽  
Yidi Chen ◽  
Nanqi Ren
Keyword(s):  
Optimal Control ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Learning Algorithm ◽  
Control Strategies ◽  
Treatment Plant ◽  
Model Verification ◽  
Operational Strategies ◽  
Q Learning ◽  
Time Optimal

The operation of a wastewater treatment plant (WWTP) is a typical complex control problem, with nonlinear dynamics and coupling effects among the variables, which renders the implementation of real-time optimal control an enormous challenge. In this study, a Q-learning algorithm with activated sludge model No. 2d-guided (ASM2d-guided) reward setting (an integrated ASM2d-QL algorithm) is proposed, and the widely applied anaerobic-anoxic-oxic (AAO) system is chosen as the research paradigm. The integrated ASM2d-QL algorithms equipped with a self-learning mechanism are derived for optimizing the control strategies (hydraulic retention time (HRT) and internal recycling ratio (IRR)) of the AAO system. To optimize the control strategies of the AAO system under varying influent loads, Q matrixes were built for both HRTs and IRR optimization through the pair of <max reward-action> based on the integrated ASM2d-QL algorithm. 8 days of actual influent qualities of a certain municipal AAO wastewater treatment plant in June were arbitrarily chosen as the influent concentrations for model verification. Good agreement between the values of the model simulations and experimental results indicated that this proposed integrated ASM2d-QL algorithm performed properly and successfully realized intelligent modeling and stable optimal control strategies under fluctuating influent loads during wastewater treatment.

Improving the efficiency of a wastewater treatment plant by fuzzy control and neural networks

2001 ◽  
Vol 43 (11) ◽  
pp. 189-196 ◽  
Author(s):  
M. Bongards
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Municipal Wastewater ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Treatment Plant ◽  
Municipal Wastewater Treatment ◽  
Controlled System ◽  
Measurement Results ◽  
Predictive Controller

One of the main problems in operating a wastewater treatment plant is the purification of the excess water from dewatering and pressing of sludge. Because of a high load of organic material and of nitrogen it has to be buffered and treated together with the inflowing wastewater. Different control strategies are discussed. A combination of neural network for predicting outflow values one hour in advance and fuzzy controller for dosing the sludge water are presented. This design allows the construction of a highly non-linear predictive controller adapted to the behaviour of the controlled system with a relatively simple and easy to optimise fuzzy controller. Measurement results of its operation on a municipal wastewater treatment plant of 60,000 inhabitant equivalents are presented and discussed. In several months of operation the system has proved very reliable and robust tool for improving the system's efficiency.

CASCADE PROCESS MODELING WITH MECHANISM-BASED HIERARCHICAL NEURAL NETWORKS

2010 ◽  
Vol 20 (01) ◽  
pp. 1-11 ◽  
Author(s):  
QIUMEI CONG ◽  
WEN YU ◽  
TIANYOU CHAI
Keyword(s):  
Neural Networks ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Learning Algorithm ◽  
Treatment Plant ◽  
Neural Model ◽  
Cascade Process ◽  
Structural Mechanism ◽  
Mechanism Model ◽  
Hierarchical Neural Networks

Cascade process, such as wastewater treatment plant, includes many nonlinear sub-systems and many variables. When the number of sub-systems is big, the input-output relation in the first block and the last block cannot represent the whole process. In this paper we use two techniques to overcome the above problem. Firstly we propose a new neural model: hierarchical neural networks to identify the cascade process; then we use serial structural mechanism model based on the physical equations to connect with neural model. A stable learning algorithm and theoretical analysis are given. Finally, this method is used to model a wastewater treatment plant. Real operational data of wastewater treatment plant is applied to illustrate the modeling approach.

Multi-criteria evaluation of wastewater treatment plant control strategies under uncertainty

2008 ◽  
Vol 42 (17) ◽  
pp. 4485-4497 ◽  
Author(s):  
Xavier Flores-Alsina ◽  
Ignasi Rodríguez-Roda ◽  
Gürkan Sin ◽  
Krist V. Gernaey
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Control Strategies ◽  
Treatment Plant ◽  
Multi Criteria Evaluation ◽  
Plant Control

An evaluation of the efficiency of the combined sewer – wastewater treatment system under transient conditions

1996 ◽  
Vol 33 (2) ◽  
pp. 199-208 ◽  
Author(s):  
W. Bauwens ◽  
P. Vanrolleghem ◽  
M. Smeets
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Control Strategies ◽  
Treatment Plant ◽  
Problem Area ◽  
Control Measures ◽  
Plant Management ◽  
Potential Control ◽  
Combined Sewer ◽  
Management Schemes

The paper considers the efficiency of alternative sewer and wastewater treatment plant management schemes with respect to the effluents to the receiving waters. The input time series for the flows and concentrations at the CSO structures and at the treatment plant intake are obtained through a continuous sewer simulation model. The wastewater treatment plant model is based on a structured dynamic model describing COD removal and final settling. Special emphasis is put on the sludge inventory of the plant since this is considered to be the main problem area under storm conditions. The methodology is illustrated on the combined sewer network of Brussels. Scenarios without and with CSO control measures in the sewer are considered. At the treatment plant, the simulation study evaluates the effect of potential control strategies such as ratio control of the RAS, step feed and retention of first flush in a storm tank.

Validation and implementation of model based control strategies at an industrial wastewater treatment plant

2001 ◽  
Vol 44 (2-3) ◽  
pp. 145-154 ◽  
Author(s):  
D. Demey ◽  
B. Vanderhaegen ◽  
H. Vanhooren ◽  
J. Liessens ◽  
L. Van Eyck ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Industrial Wastewater ◽  
Dynamic Models ◽  
Control Strategies ◽  
Treatment Plant ◽  
Practical Implementation ◽  
Industrial Wastewater Treatment ◽  
Model Based ◽  
On Line

In this paper, the practical implementation and validation of advanced control strategies, designed using model based techniques, at an industrial wastewater treatment plant is demonstrated. The plant under study is treating the wastewater of a large pharmaceutical production facility. The process characteristics of the wastewater treatment were quantified by means of tracer tests, intensive measurement campaigns and the use of on-line sensors. In parallel, a dynamical model of the complete wastewater plant was developed according to the specific kinetic characteristics of the sludge and the highly varying composition of the industrial wastewater. Based on real-time data and dynamic models, control strategies for the equalisation system, the polymer dosing and phosphorus addition were established. The control strategies are being integrated in the existing SCADA system combining traditional PLC technology with robust PC based control calculations. The use of intelligent control in wastewater treatment offers a wide spectrum of possibilities to upgrade existing plants, to increase the capacity of the plant and to eliminate peaks. This can result in a more stable and secure overall performance and, finally, in cost savings. The use of on-line sensors has a potential not only for monitoring concentrations, but also for manipulating flows and concentrations. This way the performance of the plant can be secured.

scholarly journals Control Strategies of a Wastewater Treatment Plant

2019 ◽  
Vol 52 (1) ◽  
pp. 257-262
Author(s):  
Laurentiu Luca ◽  
Ramon Vilanova ◽  
George Adrian Ifrim ◽  
Emil Ceanga ◽  
Sergiu Caraman ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Control Strategies ◽  
Treatment Plant
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