System Identification and Control Theory for Dynamic Modeling of Biological Pathways

2009 ◽  
pp. 119-132
Keyword(s):  
System Identification ◽  
Control Theory ◽  
Dynamic Modeling ◽  
Biological Pathways ◽  
And Control

System Identification and Control of the Activated Sludge Process by Use of a Statistical Model

1989 ◽  
Vol 21 (10-11) ◽  
pp. 1161-1172 ◽  
Author(s):  
M. Hiraoka ◽  
K. Tsumura
Keyword(s):  
Control System ◽  
System Identification ◽  
Statistical Model ◽  
Activated Sludge ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Ar Model ◽  
Diurnal Changes ◽  
Activated Sludge Process ◽  
And Control

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.

scholarly journals Generalized Chebyshev problem in nonholonomic mechanics and control theory

2021 ◽  
Vol 1959 (1) ◽  
pp. 012054
Author(s):  
M P Yushkov ◽  
Sh Kh Soltakhanov ◽  
V V Dodonov
Keyword(s):  
Control Theory ◽  
Nonholonomic Mechanics ◽  
Chebyshev Problem ◽  
And Control

scholarly journals Method for designing multi-input system identification signals using a compact time-frequency representation

2021 ◽  
Author(s):  
Mathias Stefan Roeser ◽  
Nicolas Fezans
Keyword(s):  
System Identification ◽  
Design Method ◽  
Flight Test ◽  
Compact Representation ◽  
Time Frequency ◽  
Stability And Control ◽  
Frequency Representation ◽  
Aerodynamic Parameters ◽  
Definition Of ◽  
And Control

AbstractA flight test campaign for system identification is a costly and time-consuming task. Models derived from wind tunnel experiments and CFD calculations must be validated and/or updated with flight data to match the real aircraft stability and control characteristics. Classical maneuvers for system identification are mostly one-surface-at-a-time inputs and need to be performed several times at each flight condition. Various methods for defining very rich multi-axis maneuvers, for instance based on multisine/sum of sines signals, already exist. A new design method based on the wavelet transform allowing the definition of multi-axis inputs in the time-frequency domain has been developed. The compact representation chosen allows the user to define fairly complex maneuvers with very few parameters. This method is demonstrated using simulated flight test data from a high-quality Airbus A320 dynamic model. System identification is then performed with this data, and the results show that aerodynamic parameters can still be accurately estimated from these fairly simple multi-axis maneuvers.

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