Multivariable modeling and control of an activated sludge process

1998 ◽  
Vol 37 (12) ◽  
pp. 149-156 ◽  
Author(s):  
Carl-Fredrik Lindberg

This paper contains two contributions. First it is shown, in a simulation study using the IAWQ model, that a linear multivariable time-invariant state-space model can be used to predict the ammonium and nitrate concentration in the last aerated zone in a pre-denitrifying activated sludge process. Secondly, using the estimated linear model, a multivariable linear quadratic (LQ) controller is designed and used to control the ammonium and nitrate concentration.

2013 ◽  
Vol 791-793 ◽  
pp. 818-821
Author(s):  
Shi Li ◽  
Xi Ju Zong ◽  
Yan Hu

This paper is concerns with the study of modeling and control of biochemical reactor. Firstly, a mathematical model is established for a typical biochemical reactor, the mass balance equations are established individually for substrate concentration and biomass concentration. Then, the model is linearized at the steady-state point, two linear models are derived: state space model and transfer function model. The transfer function model is used in internal model control (IMC), where the filter parameter is selected and discussed. The state space model is applied in model predictive control (MPC), where controller parameters of control prediction horizon length and constraint of control variable variation are discussed.


2013 ◽  
Vol 846-847 ◽  
pp. 69-72
Author(s):  
Shi Li ◽  
Xi Ju Zong ◽  
Yan Hu

This paper is concerns with the study of modeling and control of sludge pyrolysis in a fluidized bed reactor. Firstly, a mathematical model is established for sludge pyrolysis in a fluidized bed furnace, mass balance and energy equations are established. Then, the model is linearized at the steady-state point, two linear models are derived: state space model and transfer function model. The transfer function model is used in internal model control (IMC), where the filter parameter is selected and discussed. The state space model is applied in model predictive control (MPC), where controller parameters of prediction horizon length and control horizon length are discussed.


1989 ◽  
Vol 21 (10-11) ◽  
pp. 1161-1172 ◽  
Author(s):  
M. Hiraoka ◽  
K. Tsumura

The authors have been developing a hierarchical control system for the activated sludge process which consists of an upper level system controlling long-term seasonal variations, a control system of intermediate level aiming at optimization of the process and a control system of lower level controlling diurnal changes or hourly fluctuations. The control system using the multi-variable statistical model is one of the most appropriate control systems based on the modern control theory, for applying the lower level control of the activated sludge process. This paper introduces our efforts for developing the reliable data acquisition system, the control experiments applying the AR-model, one of the statistical models which were conducted at a pilot plant and present studies on the system identification and control at a field sewage treatment plant.


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