Semi-Empirical Modeling of Non-Linear Dynamic Systems through Identification of Operating Regimes and Local Models

Johansen, Tor Arne; Foss, Bjarne A.

doi:10.1007/978-1-4471-3066-6_6

Cited by 24 publications

(9 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There were no noticeable differences for state variable predictions using the training data set and the two validation data sets. It is believed that this approach offers an advantage over the novel approach by Johansen and Foss [14] who proposed a model representation based on the interpolation of several simple local models.…”

Section: Resultsmentioning

confidence: 99%

“…In this investigation, the values of the coef®cients used to perform the simulation were identical to those used by Johansen and Foss [14]. For the sake of completeness, these values are reproduced in Table 1.…”

Section: List Of Symbolsmentioning

confidence: 96%

“…where nrY t is the surface apex density (# apices/lm 2 ) and XrY t is the surface biomass density (lgalm 2 ), both functions of radial location r and time t. Equation (14) states that the local growth of biomass is supported by the growing apices and it is therefore proportional to the hyphal extension rate (V h ) at which these apices propagate. The term (qpd 2 a4) is the biomass per unit length of mycelia which, when multiplied by the propagation velocity, gives the increase of biomass density per unit time.…”

Section: Brief Description Of the Systemmentioning

confidence: 99%

“…Table 4 presents the values of the diffusion coef®cient that were obtained with the general hybrid model and the values that were obtained by ®tting the phenomenological model (Eqs. (14) and (15)), one experiment at the time. These results show that the hybrid model is general as it provides a diffusion coef®cient as accurate as if they were individually ®tted.…”

Section: Brief Description Of the Systemmentioning

confidence: 99%

See 3 more Smart Citations

A hybrid representation approach for modelling complex dynamic bioprocesses

Thibault

Acuña

Pérez-Correa

et al. 2000

Bioprocess Engineering

View full text Add to dashboard Cite

This paper considers the use of hybrid models to represent the dynamic behaviour of biotechnological processes. Each hybrid model consists of a set of non linear differential equations and a neural model. The set of differential equations attempts to describe as much as possible the phenomenology of the process whereas neural networks model predict some key parameters that are an essential part of the phenomenological model. The neural model is obtained indirectly, that is, using the prediction errors of one or more state variables to adjust its weights instead of successive presentations of inputoutput data of the neural network. This approach allows to use actual measurements to derive a suitable neural model that not only represents the variation of some key parameters but it is also able to partly include dynamic behaviour unaccounted for by the phenomenological model. The approach is described in detail using three test cases:(1) the fermentation of glucose to gluconic acid by the micro-organism Pseudomonas ovalis, (2) the growth of ®lamentous fungi in a solid state fermenter, and (3) the propagation of ®lamentous fungi growing on a 2-D solid substrate. Results for the three applications clearly demonstrate that using a hybrid model is a viable alternative for modelling complex biotechnological bioprocesses.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: List Of Symbolsmentioning

confidence: 96%

Section: Brief Description Of the Systemmentioning

confidence: 99%

Section: Brief Description Of the Systemmentioning

confidence: 99%

See 2 more Smart Citations

A hybrid representation approach for modelling complex dynamic bioprocesses

Thibault

Acuña

Pérez-Correa

et al. 2000

Bioprocess Engineering

View full text Add to dashboard Cite

show abstract

“…Studies of this reaction concerned with the effect of K L a on productivity have reported that, at steady state, the rate of oxygen absorption is proportional to the rate of production of gluconic acid without the interference of side reactions [4]. The overall mechanism can be expressed as follows [5]:…”

Section: Gluconic Acid Production Modelmentioning

confidence: 99%

Multicriteria optimization of gluconic acid production using net flow

Halsall-Whitney

Taylor

Thibault

2003

Bioprocess Biosyst Eng

View full text Add to dashboard Cite

The biochemical process industry is often confronted with the challenge of making decisions in an atmosphere of multiple and conflicting objectives. Recent innovations in the field of operations research and systems science have yielded rigorous multicriteria optimization techniques that can be successfully applied to the field of biochemical engineering. These techniques incorporate the expert's experience into the optimization routine and provide valuable information about the zone of possible solutions. This paper presents a multicriteria optimization strategy that generates a Pareto domain, given a set of conflicting objective criteria, and determines the optimal operating region for the production of gluconic acid using the net flow method (NFM). The objective criteria include maximizing the productivity and concentration of gluconic acid, while minimizing the residual substrate. Three optimization strategies are considered. The first two strategies identify the optimal operating region for the process inputs. The results yielded an acceptable compromise between productivity, gluconic acid concentration and residual substrate concentration. Fixing the process inputs representing the batch time, initial substrate concentration and initial biomass equal to their optimal values, the remaining simulations were used to study the sensitivity of the optimum operating region to changes in the oxygen mass transfer coefficient, K(L) a, by utilizing a multi-level K(L) a strategy. The results show that controlling K(L) a during the reaction reduced the production of biomass, which in turn resulted in increased productivity and concentration of gluconic acid above that of a fixed K(L) a.

show abstract