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Investigation of process parameters and development of a mathematical model for the purposes of control design and implementation for a wastewater treatment process
Author(s)
Du Plessis, Sydney Charles
Date Issued
2009
Type
Thesis
Publisher
Cape Peninsula University of Technology
Abstract
The problem for effective and optimal control of wastewater treatment plants is very
important recently because of the increased requirements to the quality of the effluent.
The activated sludge process is a type of wastewater process characterized with
complex dynamics and because of this proper control design and implementation
strategies are necessary and important for its operation. Since the early seventies, when
a major leap forward was made by the widespread introduction of dissolved oxygen
control, little progress has been made.
The most critical phase in the solution of any control problem is the modelling stage. The
primary building block of any modern control exercise is to construct and identify a
model for the system to be controlled. The existing full Activated Sludge Model 1
(ASM1) and especially University of Cape Town (UCT) models of the biological
processes in the activated sludge process, called in the thesis biological models, are
highly complex because they are characterised with a lot of variables that are difficult to
be measured on-line, complex dependencies and nonlinear interconnections between
the biological variables, many kinetic parameters that are difficult to be determined,
different time scales for the process dynamics.
The project considers reduction of the impact of the complexity of the process model
over the methods for control design and proposes a solution to the above difficulties by
development of a reduced model with small number of variables, but still with the same
characteristics as the original full model for the purposes of real time control design.
Then the research problem can be stated in the following way: To develop mathematical
methods, algorithms and programmes for transformation of the complex biological and
mass balance models of the activated sludge process into simpler reduced models of
the process convenient to be used for optimal parameter estimation, control design and
control implementation in real- time.
important recently because of the increased requirements to the quality of the effluent.
The activated sludge process is a type of wastewater process characterized with
complex dynamics and because of this proper control design and implementation
strategies are necessary and important for its operation. Since the early seventies, when
a major leap forward was made by the widespread introduction of dissolved oxygen
control, little progress has been made.
The most critical phase in the solution of any control problem is the modelling stage. The
primary building block of any modern control exercise is to construct and identify a
model for the system to be controlled. The existing full Activated Sludge Model 1
(ASM1) and especially University of Cape Town (UCT) models of the biological
processes in the activated sludge process, called in the thesis biological models, are
highly complex because they are characterised with a lot of variables that are difficult to
be measured on-line, complex dependencies and nonlinear interconnections between
the biological variables, many kinetic parameters that are difficult to be determined,
different time scales for the process dynamics.
The project considers reduction of the impact of the complexity of the process model
over the methods for control design and proposes a solution to the above difficulties by
development of a reduced model with small number of variables, but still with the same
characteristics as the original full model for the purposes of real time control design.
Then the research problem can be stated in the following way: To develop mathematical
methods, algorithms and programmes for transformation of the complex biological and
mass balance models of the activated sludge process into simpler reduced models of
the process convenient to be used for optimal parameter estimation, control design and
control implementation in real- time.
Additional information
(DTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009.
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203167309-du Plessis-Sydney Charles-D.Tech-Electrical-Engineering-Eng-2009-9001598.pdf
Description
Theses
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Format
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