Modelling and Adaptive Control of a Continuous Anaerobic Fermentation Process

Bastin, Georges; Dochain, Denis; Haest, M.; Installé, M.; Opdenacker, Ph.

doi:10.1016/b978-0-08-029978-5.50040-9

Cited by 9 publications

(4 citation statements)

References 3 publications

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“…Therefore, we did not expect all 12 parameters in our model to be identi®able. Bastin et al (1982) and Chalon et al (1982) applied model transformations to determine which parameter combinations were identi®able. Unfortunately, even for their transformed model, it was still unclear whether at least the transformed parameters were identi®able.…”

Section: Theoretical Identifiabilitymentioning

confidence: 99%

Quantitative analyses of anaerobic wastewater treatment processes: Identifiability and parameter estimation

Noykova

Müller

Gyllenberg

et al. 2002

Biotech & Bioengineering

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We investigated the problem of identifying the parameters of a nonlinear fifth order model describing the population dynamics of two main bacterial groups in an anaerobic wastewater treatment process. In addition to addressing problems concerning structural and practical identifiability, we also analyzed how mathematical descriptions of bacterial population dynamics can model real data. Using three data sets recorded under different experimental conditions, we estimated important biochemical parameters and demonstrated that our model could describe the data successfully. Parameters, which are simultaneously determined using information from all three experiments, have more reliable estimates. We conclude that, after appropriate estimation, this model can be used for optimization and the control of continuous processes.

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Section: Theoretical Identifiabilitymentioning

confidence: 99%

Quantitative analyses of anaerobic wastewater treatment processes: Identifiability and parameter estimation

Noykova

Müller

Gyllenberg

et al. 2002

Biotech & Bioengineering

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show abstract

“…In 1979, McInnis et al were among the first to report an adaptive controller using a microcomputer to control dissolved oxygen levels in biological wastewater treatment [74] . Bastin et al discussed an adaptive controller to regulate an anaerobic fermentation process for waste degradation in 1983 [82] . One year later, in 1984, Dochain and Bastin summarized adaptive control algorithms for nonlinear bacterial growth systems to control substrate concentration or production rate.…”

Section: Modeling In Process Controlmentioning

confidence: 99%

History and Evolution of Modeling in Biotechnology: Modeling & Simulation, Application and Hardware Performance

Noll

Henkel

2020

Computational and Structural Biotechnology Journal

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“…Many mathematical linear and non-linear models are available in the literature [2,6,8,13,15,19], but in the present work we investigate only one model, related to a three stage reaction scheme and including substrate inhibition of methanogenic bacteria.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis and parameter estimation in a model of anaerobic waste water treatment processes with substrate inhibition

Noykova

Gyllenberg

2000

Bioprocess Engineering

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Anaerobic waste water treatment processes are commonly presented by the ®fth order Hill and Barth nonlinear model, describing three main stages of anaerobic digestion. The model investigated in the present work is a modi®ed version of the Hill and Barth model, which includes substrate inhibition of growth of methanogenic bacteria. Parameter estimation of this model is a dif®cult problem because of the high number of parameters to be estimated and the rather restricted information concerning the variables.The aim of the present work is to use sensitivity theory to ®nd a method for selecting the most signi®cant parameters. In particular, we develop a sensitivity model for anaerobic digestion using relative sensitivity functions. Simulation results from the sensitivity model show that the number of parameters to be estimated can be reduced from 12 to 4. We suggest a 2-step procedure for parameter estimation, which is also based on sensitivity analysis. This procedure gives results, which allow for off-line determination of parameter values if the experimental data for biogas production rate are known.

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Modelling and Adaptive Control of a Continuous Anaerobic Fermentation Process

Cited by 9 publications

References 3 publications

Quantitative analyses of anaerobic wastewater treatment processes: Identifiability and parameter estimation

Quantitative analyses of anaerobic wastewater treatment processes: Identifiability and parameter estimation

History and Evolution of Modeling in Biotechnology: Modeling & Simulation, Application and Hardware Performance

Sensitivity analysis and parameter estimation in a model of anaerobic waste water treatment processes with substrate inhibition

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