scholarly journals Software Sensors for Biomass Concentration Estimation in Filamentous Microorganism Cultivation Process

2019 ◽  
Vol 33 (1) ◽  
pp. 141-151 ◽  
Author(s):  
Pavel Hrnčiřík ◽  
Tomáš Moucha ◽  
Jan Mareš ◽  
Jan Náhlík ◽  
Dagmar Janáčová
Keyword(s):  
Linear Regression ◽  
Heat Production ◽  
Process Model ◽  
Biomass Concentration ◽  
Main Process ◽  
Software Sensor ◽  
Enthalpy Balance ◽  
Filamentous Microorganisms ◽  
Software Sensors ◽  
On Line

In this study, the potential of two software sensors for on-line estimation of biomass concentration during cultivation of filamentous microorganisms is examined. The first sensor is based on common bioreactor off-gas analyses, and uses the assumption of the biomass concentration linear dependence on the square root of cumulative O2 consumption. Parameters of the semi-empirical data-driven software sensor based on off-gas analysis were calculated from experimental cultivation data using linear regression. The second sensor is based on biocalorimetry, i.e., the on-line calculation of metabolic heat flux from general enthalpy balance of the bioreactor. The software sensor based on biocalorimetry thus essentially represents a model-driven approach, making use of a fundamental process model based on the enthalpy balance around the bioreactor. This approach has been combined with the experimental identification of the specific biomass heat production, which represents the main process-specific parameter of the software sensor based on biocalorimetry. For this sensor, the accuracy requirements on the process variable on-line measurements were also analysed. The experimental data from the pilot-scale antibiotics Nystatin production by a bacterium Streptomyces noursei were used to calculate the specific bioprocess heat production value using linear regression. The achieved results enabled us to propose a new on-line indicator calculated as the ratio of the outputs of both sensors, which can serve as a timely warning of the risk of undesired nutritional conditions of a culture characterized as underfeeding.

On-line process-model-based control of a plasma etcher

1992 ◽  
Author(s):  
Michael E. Parten ◽  
R. R. Rhinehart ◽  
Vikram Singh
Keyword(s):  
Process Model ◽  
Model Based Control ◽  
Model Based ◽  
On Line ◽  
Line Process

Online estimation of VFA, alkalinity and bicarbonate concentrations by electrical conductivity measurement during anaerobic fermentation

2012 ◽  
Vol 65 (7) ◽  
pp. 1281-1289 ◽  
Author(s):  
Cesar-Arturo Aceves-Lara ◽  
Eric Latrille ◽  
T. Conte ◽  
Jean-Philippe Steyer
Keyword(s):  
Electrical Conductivity ◽  
Hydrogen Production ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Anaerobic Fermentation ◽  
Simple Linear Regression ◽  
Conductivity Measurements ◽  
Bicarbonate Concentration ◽  
On Line

This paper describes the use of electrical conductivity for measurement of volatile fatty acids (VFA), alkalinity and bicarbonate concentrations, during the anaerobic fermentation process. Two anaerobic continuous processes were studied: the first was a laboratory reactor for hydrogen production from molasses and the second was a pilot process for anaerobic digestion (AD) of vinasses producing methane. In the hydrogen production process, the total VFA concentration, but not bicarbonate concentration, was well estimated from the on-line electrical conductivity measurements with a simple linear regression model. In the methane production process, the bicarbonate concentration and the VFA concentration were well estimated from the simultaneous on-line measurements of pH and electrical conductivity by means of non-linear regression with neural network models. Moreover, the total alkalinity concentration was well estimated from electrical conductivity measurements with a simple linear regression model. This demonstrates the use of electrical conductivity for monitoring the AD processes.

An Evaluation of the Kenz Calorie Counter during Progressive Treadmill Exercise in Adults and Children

1996 ◽  
Vol 8 (2) ◽  
pp. 156-165 ◽  
Author(s):  
Nicholas J. Walters ◽  
David A. Brodie
Keyword(s):  
Linear Regression ◽  
Energy Expenditure ◽  
Body Mass ◽  
Correction Factor ◽  
Treadmill Exercise ◽  
Gas Analysis ◽  
Age Group ◽  
Measured Energy ◽  
Adults And Children ◽  
On Line

The purpose of this study was to assess the validity of data derived from the Kenz calorie counter during progressive, incremental treadmill exercise. Direct comparisons were made with calories calculated from on-line gas analysis. The subjects were 18 adults, 18 postadolescent children, and 24 preadolescent children. Linear regression (r2 > .95) showed a progressive deviation away from a 1:1 relationship between Kenz data and V̇O2 data with increasing age of subject which remained when standardized to kcal · kg−1 body mass or kcal · m−2 · hour−1. The Kenz calorie counter, after applying an age group correction factor, can thus be used as a suitable analog for measured energy expenditure.

Two-Step Process Identification With Correlation Analysis and Least-Squares Parameter Estimation

1974 ◽  
Vol 96 (4) ◽  
pp. 426-432 ◽  
Author(s):  
R. Isermann ◽  
U. Bauer
Keyword(s):  
Correlation Analysis ◽  
Process Model ◽  
A Priori ◽  
Industrial Process ◽  
Computation Time ◽  
Small Computer ◽  
Nonparametric Model ◽  
Identification Method ◽  
On Line ◽  
Process Computer

An identification method is described which first identifies a linear nonparametric model (crosscorrelation function, impulse response) by correlation analysis and then estimates the parameters of a parametric model (discrete transfer function) and also includes a method for the detection of the model order and the time delay. The performance, the computational expense and the overall reliability of this method is compared with five other identification methods. This two-step identification method, which can be applied off-line or on-line, is especially suited to identification by process computers, since it has the properties: Little a priori knowledge about the structure of the process model; very short computation time; small computer storage; no initial values of matrices and parameters are necessary and no divergence is possible for the on-line version. Results of an on-line identification of an industrial process with a process computer are shown.

scholarly journals Model-Based Autonomous Navigation with Moment of Inertia Estimation for Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2467 ◽  
Author(s):  
Hery Mwenegoha ◽  
Terry Moore ◽  
James Pinchin ◽  
Mark Jabbal
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Navigation System ◽  
Process Model ◽  
Unscented Kalman Filter ◽  
Low Cost ◽  
Moment Of Inertia ◽  
Model Parameters ◽  
Main Process ◽  
Model Based ◽  
Aerial Vehicles

The dominant navigation system for low-cost, mass-market Unmanned Aerial Vehicles (UAVs) is based on an Inertial Navigation System (INS) coupled with a Global Navigation Satellite System (GNSS). However, problems tend to arise during periods of GNSS outage where the navigation solution degrades rapidly. Therefore, this paper details a model-based integration approach for fixed wing UAVs, using the Vehicle Dynamics Model (VDM) as the main process model aided by low-cost Micro-Electro-Mechanical Systems (MEMS) inertial sensors and GNSS measurements with moment of inertia calibration using an Unscented Kalman Filter (UKF). Results show that the position error does not exceed 14.5 m in all directions after 140 s of GNSS outage. Roll and pitch errors are bounded to 0.06 degrees and the error in yaw grows slowly to 0.65 degrees after 140 s of GNSS outage. The filter is able to estimate model parameters and even the moment of inertia terms even with significant coupling between them. Pitch and yaw moment coefficient terms present significant cross coupling while roll moment terms seem to be decorrelated from all of the other terms, whilst more dynamic manoeuvres could help to improve the overall observability of the parameters.

Effect of co-substrate, biomass and sulfate concentration on the performance of a control strategy used to determine the anaerobic stage length of an anaerobic/aerobic SBR degrading p-nitrophenol

2005 ◽  
Vol 52 (1-2) ◽  
pp. 441-447 ◽  
Author(s):  
G. Buitrón ◽  
G. Moreno ◽  
M.E. García ◽  
J. Moreno
Keyword(s):  
Significant Influence ◽  
Control Strategy ◽  
Reduction Potential ◽  
Biomass Concentration ◽  
Sulfate Concentration ◽  
Oxidation Reduction ◽  
Oxidation Reduction Potential ◽  
Acid Ratio ◽  
Line Measurement ◽  
On Line

The effect of the p-nitrophenol to propionic acid ratio, the biomass concentration, and the presence of sulfates on the performance of a control strategy of an anaerobic/aerobic SBR degrading p-nitrophenol was studied. The duration of the anaerobic stage was controlled by an algorithm based on the on-line measurement of the oxidation-reduction potential, which indicates the end of the reduction of p-nitrophenol to p-aminophenol. It was observed that no significant influence on the performance of the algorithm was found when the co-substrate, the biomass concentration and the presence of sulfates were varied, indicating the robustness of the control strategy. Only for the case when a low concentration of co-substrate was used, was there no transformation of p-nitrophenol.

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