1,721,018 research outputs found
Investigation of process parameters and development of a mathematical model for the purposes of control design and implementation for a wastewater treatment process
No full textThesis (DTech (Electrical Engineering))--Cape Peninsula University of Technology, 2009The problem for effective and optimal control of wastewater treabnent 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 modem 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
Optimal PID control of the dissolved oxygen concentration in the wastewater treatment plant
No full textThe biological process for treatment of the municipal wastewater, the Activated Sludge process, is considered. The efficient performance of the water treatment process depends on the optimal control of the concentration of oxygen in the aeration tanks. This paper describes application of two standard PID controllers tuning methods for control of the nonlinear dissolved oxygen concentration process as a part of an adaptive optimal control strategy. Procedures for real time implementation of the tuning methods and the calculated control in the frameworks of Adroit SCADA and Matlab/Simulinks software are described. The calculations are done for COST benchmark and the University of Cape Town process structures and the ASM1 biological model
Method for real time optimal control of the activated sludge process
No full texthe problem for optimal control of the activated sludge process based on ASM1 model is considered. The objective is to determine a method for real time calculation of an optimal dissolved oxygen trajectory and the corresponding optimal state trajectories subject to minimization of both the deviations from the effluent requirements and the control energy consumption. The paper presents the developed reduced biological model of the activated sludge process, Athlone plant mass balance model and method for the optimal control problem solution in a real time. The optimal control problem solution is calculated in Matlab environment and the real time control is implemented in Adroit SCADA environment
Optimal PID control of the dissolved oxygen concentration in the wastewater treatment plant
No full textThe biological process for treatment of the municipal wastewater, the Activated Sludge process, is considered. The efficient performance of the water treatment process depends on the optimal control of the concentration of oxygen in the aeration tanks. This paper describes application of two standard PID controllers tuning methods for control of the nonlinear dissolved oxygen concentration process as a part of an adaptive optimal control strategy. Procedures for real time implementation of the tuning methods and the calculated control in the frameworks of Adroit SCADA and Matlab/Simulinks software are described. The calculations are done for COST benchmark and the University of Cape Town process structures and the ASM1 biological model
Method for real time optimal control of the activated sludge process
No full texthe problem for optimal control of the activated sludge process based on ASM1 model is considered. The objective is to determine a method for real time calculation of an optimal dissolved oxygen trajectory and the corresponding optimal state trajectories subject to minimization of both the deviations from the effluent requirements and the control energy consumption. The paper presents the developed reduced biological model of the activated sludge process, Athlone plant mass balance model and method for the optimal control problem solution in a real time. The optimal control problem solution is calculated in Matlab environment and the real time control is implemented in Adroit SCADA environment
Robust non-linear networked control of wastewater distributed systems
No full textCPUT Water Research Semina
Neural networks for prediction of wastewater treatment plant influent disturbances
No full textIn order to develop an effective control strategy for the activated sludge process (ASP) of a wastewater treatment plant, an understanding of the nature of the influent load disturbances to the wastewater treatment plant is necessary. The wastewater treatment processes are dynamic and the interrelationships between variables are very complex. The values of the influent disturbances are usually measured off-line in a laboratory, as there are still no reliable on-line sensors available. This work proposes development of a neural network model for prediction of the values of the influent disturbances, which ultimately affect the activated sludge process. Three different dynamic multilayer perceptron feed-forward neural network models and three recurrent neural networks are developed for the prediction of the influent disturbances of chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN) and flowrate respectively. The predictive performance of the multi-layer perceptron is compared to that of the recurrent neural network
Investigation on the impact of the penalty factors over solution of the dispatch optimization problem
No full text2013 IEEE International Conference on Industrial Technology (ICIT 2013
Neural networks for prediction of wastewater treatment plant influent disturbances
No full textIn order to develop an effective control strategy for the activated sludge process (ASP) of a wastewater treatment plant, an understanding of the nature of the influent load disturbances to the wastewater treatment plant is necessary. The wastewater treatment processes are dynamic and the interrelationships between variables are very complex. The values of the influent disturbances are usually measured off-line in a laboratory, as there are still no reliable on-line sensors available. This work proposes development of a neural network model for prediction of the values of the influent disturbances, which ultimately affect the activated sludge process. Three different dynamic multilayer perceptron feed-forward neural network models and three recurrent neural networks are developed for the prediction of the influent disturbances of chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN) and flowrate respectively. The predictive performance of the multi-layer perceptron is compared to that of the recurrent neural network
Comparison of the Lagrange's and particle swarm optimisation solutions of an economic emission dispatch problem with transmission constraints
No full textThe power demand is increased rapidly and hence the power systems become more complex, so it is necessary to solve the dispatch problem with less computation time. This paper uses the optimization approach (Lagrange's) and random variables selection approach Particle Swarm Optimisation (PSO) to solve the dispatch problem with transmission constraints and to compare the obtained solution and the time for its calculation. Formulation of a bi-criteria Combined Economic Emission Dispatch (CEED) problem is given. The application of Lagrange's and PSO methods to the CEED problem is described and the algorithms for calculations are given. The computational time of the Lagrange's algorithm depends on the selection of the initial values of the Lagrange's variable (λ), and on the swarms, positions, and velocity selection in PSO algorithm. The IEEE 30 bus system is considered to validate the simulation results in MATLAB environment. It concludes that Lagrange's algorithm provides better results for CEED problem in comparison to the PSO algorithm
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