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Investigation and development of methods for optimal control of the activated sludge process
Author(s)
Kujane, Koketso Portia
Date Issued
2009
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
This project was started as a result of strict environmental and health regulations together
with a demand tor cost effective operation of wastewater treatment plants (VVWTPs). The
main aim of this project is how to keep effluent concentration below a prescribed limit at the
lowest possible cost. Due to large fluctuations in the quality and quantity of the influent
concentrations, traditional control methods are not adequate to achieve this aim The major
drawback with these methods is that the disturbances affect the process before the controller
has time to correct the error (Olsson and Newell, 1999: 454). This problem is addressed
through the use of modern control systems.
Modern control systems are model based predictive algorithms arranged as feed-forward
controllers (Olsson and Newell. 1999: 454). Normally a controller is equipped with a constant
set point; the goal In this project is to calculate an optimal DO trajectory that may be sampled
to provide a varying optimal set-point for the Activated Sludge Process, In this project an
optimal control problem Is formulated using DO concentration as a control variable. This
requires a model of the process to be controlled a mathematical expressions of the
limitations on the process input and output variables and finally the objective functional. which
consists of the objectives of the control.
The structures of the Benchmark plant (developed within the COST 682 working group) and
the Athlone WWTPs are used to implement this opt.mat control strategy in MATLAB. The
plant's full models are developed based on the mass balance principle incorporating the
activated sludge biological models: ,ASM1, ASM2, ASM2d and ASM3 (developed by the IWA
working groups). To be able to develop a method that may later on be used for online
control, the full models are reduced based on the technique In Lukasse (1996). To ensure
that the reduced models keep the same prediction capabilities as the full models, parameters
of the reduced models are calculated based on the Least Squares principle, The formulated
optimal control problem is solved based on the decompostion-coorcdination method that
involves time decomposition in a two layer structure.
MATLAB software [5 developed to solve the problems for parameter estimation. fun and
reduced mode! simulation. and optimal control calculation for the considered different cases
of plant structures and biological models. The obtained optimal 00 trajectories produced the
effluent state trajectories within prescribed requirements. These DO trajectories may be
implemented in different SCADA systems to be tracked as set points or desired trajectories
by different types of controllers.
with a demand tor cost effective operation of wastewater treatment plants (VVWTPs). The
main aim of this project is how to keep effluent concentration below a prescribed limit at the
lowest possible cost. Due to large fluctuations in the quality and quantity of the influent
concentrations, traditional control methods are not adequate to achieve this aim The major
drawback with these methods is that the disturbances affect the process before the controller
has time to correct the error (Olsson and Newell, 1999: 454). This problem is addressed
through the use of modern control systems.
Modern control systems are model based predictive algorithms arranged as feed-forward
controllers (Olsson and Newell. 1999: 454). Normally a controller is equipped with a constant
set point; the goal In this project is to calculate an optimal DO trajectory that may be sampled
to provide a varying optimal set-point for the Activated Sludge Process, In this project an
optimal control problem Is formulated using DO concentration as a control variable. This
requires a model of the process to be controlled a mathematical expressions of the
limitations on the process input and output variables and finally the objective functional. which
consists of the objectives of the control.
The structures of the Benchmark plant (developed within the COST 682 working group) and
the Athlone WWTPs are used to implement this opt.mat control strategy in MATLAB. The
plant's full models are developed based on the mass balance principle incorporating the
activated sludge biological models: ,ASM1, ASM2, ASM2d and ASM3 (developed by the IWA
working groups). To be able to develop a method that may later on be used for online
control, the full models are reduced based on the technique In Lukasse (1996). To ensure
that the reduced models keep the same prediction capabilities as the full models, parameters
of the reduced models are calculated based on the Least Squares principle, The formulated
optimal control problem is solved based on the decompostion-coorcdination method that
involves time decomposition in a two layer structure.
MATLAB software [5 developed to solve the problems for parameter estimation. fun and
reduced mode! simulation. and optimal control calculation for the considered different cases
of plant structures and biological models. The obtained optimal 00 trajectories produced the
effluent state trajectories within prescribed requirements. These DO trajectories may be
implemented in different SCADA systems to be tracked as set points or desired trajectories
by different types of controllers.
Additional information
Thesis (MTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009
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