Neural network applications in non-linear modelling of (bio)chemical processes
TLDR
The objective of this paper is to review some of the most widely used approaches to neural-network-based modelling, including plain black box as well as hybrid neural network — first principles modelling.Abstract:
In recent years, neural networks have attracted much attention for their potential to address a number of difficult problems in modelling and controlling nonlinear dynamic systems, especially in (bio) chemical engineering. The objective of this paper is to review some of the most widely used approaches to neural-network-based modelling, including plain black box as well as hybrid neural network — first principles modelling. Two specific application examples are used for illustration purposes: a simple tank level-control system is studied in simulation while a challenging bioprocess application is investigated based on experimental data. These applications allow some original concepts and techniques to be introduced.read more
Citations
More filters
Journal ArticleDOI
Optimization of fed-batch recombinant yeast fermentation for ethanol production using a reduced dynamic flux balance model based on artificial neural networks
Reza Eslamloueyan,Payam Setoodeh +1 more
TL;DR: The results show that in similar conditions a small deviation in each operating parameter from its optimal value may lead to considerable decrease in ethanol productivity.
Journal ArticleDOI
Results of application of artificial neural networks in predicting geo-mechanical properties of stabilised clays - A Review
TL;DR: The findings from this study show that ANNs are becoming well known in dealing with the problem of mathematical modelling involving nonlinear functions due to their robust data analysis and correlation capabilities and have been successfully applied to the stabilisation of clays with high performance.
Journal ArticleDOI
Digitally enabled approaches for the scale up of mammalian cell bioreactors
TL;DR: In this paper , a review of the state of the art in digital advances in scaling bioreactors and the advantages and limitations of scaling techniques is outlined, and the role of hybrid modelling and digital twins and their potential in bioprocess development are explored.
Journal ArticleDOI
Neural network-based software sensors for the estimation of key components in brewery wastewater anaerobic digester: an experimental validation.
TL;DR: This work focused on the experimental validation of software sensors with a view to improving on-line anaerobic digester monitoring, and demonstrated the capacity of the MH-RBF-ANN to correctly predict the key-component evolutions and to improve the estimation accuracy.
Journal ArticleDOI
Optimization of modified rotameter using hall probe sensor with respect to liquid density and its calibration using artificial neural network
Sunita Sinha,Nirupama Mandal +1 more
TL;DR: A modified rotameter with Hall Probe sensor is used as a measuring instrument and the measuring system is calibrated using ANN, which results in obtaining the output close to the desired output.
References
More filters
Journal ArticleDOI
Learning representations by back-propagating errors
TL;DR: Back-propagation repeatedly adjusts the weights of the connections in the network so as to minimize a measure of the difference between the actual output vector of the net and the desired output vector, which helps to represent important features of the task domain.
Journal ArticleDOI
Finding Structure in Time
TL;DR: A proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory and suggests a method for representing lexical categories and the type/token distinction is developed.
Journal ArticleDOI
On the approximate realization of continuous mappings by neural networks
TL;DR: It is proved that any continuous mapping can be approximately realized by Rumelhart-Hinton-Williams' multilayer neural networks with at least one hidden layer whose output functions are sigmoid functions.
Journal ArticleDOI
Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
TL;DR: The paper presents an SA algorithm that is based on a simultaneous perturbation gradient approximation instead of the standard finite-difference approximation of Keifer-Wolfowitz type procedures that can be significantly more efficient than the standard algorithms in large-dimensional problems.
Book
On-Line Estimation and Adaptive Control of Bioreactors
Georges Bastin,Denis Dochain +1 more
TL;DR: The general dynamical model of bioreactors was extended to include extended Luenberger and Kalman observers and asymptotic observers for state estimation when the reaction rates are unknown, and a general solution to the linearizing control problem for a class of CST bioreacts was found.
Related Papers (5)
The use of artificial neural networks in materials science based research
Wei Sha,K.L. Edwards +1 more
Artificial neural networks: theoretical background and pharmaceutical applications: a review.
Marek Wesolowski,Bogdan Suchacz +1 more