[HTML][HTML] Review and classification of recent observers applied in chemical process systems
Observers are computational algorithms designed to estimate unmeasured state variables
due to the lack of appropriate estimating devices or to replace high-priced sensors in a plant …
due to the lack of appropriate estimating devices or to replace high-priced sensors in a plant …
Data-driven control: Overview and perspectives
W Tang, P Daoutidis - 2022 American Control Conference …, 2022 - ieeexplore.ieee.org
Process systems are characterized by nonlinearity, uncertainty, large scales, and also the
need of pursuing both safety and economic optimality in operations. As a result they are …
need of pursuing both safety and economic optimality in operations. As a result they are …
[HTML][HTML] Development of a hybrid model for a partially known intracellular signaling pathway through correction term estimation and neural network modeling
Developing an accurate first-principle model is an important step in employing systems
biology approaches to analyze an intracellular signaling pathway. However, an accurate first …
biology approaches to analyze an intracellular signaling pathway. However, an accurate first …
[HTML][HTML] Estimating parameters of photovoltaic models using accurate turbulent flow of water optimizer
Recently, the use of diverse renewable energy resources has been intensively expanding
due to their technical and environmental benefits. One of the important issues in the …
due to their technical and environmental benefits. One of the important issues in the …
[HTML][HTML] Parameter identifiability analysis and visualization in large-scale kinetic models of biosystems
Background Kinetic models of biochemical systems usually consist of ordinary differential
equations that have many unknown parameters. Some of these parameters are often …
equations that have many unknown parameters. Some of these parameters are often …
[HTML][HTML] Robust and efficient parameter estimation in dynamic models of biological systems
Background Dynamic modelling provides a systematic framework to understand function in
biological systems. Parameter estimation in nonlinear dynamic models remains a very …
biological systems. Parameter estimation in nonlinear dynamic models remains a very …
Distributed moving horizon state estimation of two-time-scale nonlinear systems
In this paper, we focus on distributed moving horizon estimation (DMHE) for a class of two-
time-scale nonlinear systems described in the framework of singularly perturbed systems. By …
time-scale nonlinear systems described in the framework of singularly perturbed systems. By …
[HTML][HTML] Data-driven discovery of the governing equations of dynamical systems via moving horizon optimization
Discovering the governing laws underpinning physical and chemical phenomena entirely
from data is a key step towards understanding and ultimately controlling systems in science …
from data is a key step towards understanding and ultimately controlling systems in science …
[HTML][HTML] Comprehensive review of models and methods for inferences in bio-chemical reaction networks
The key processes in biological and chemical systems are described by networks of
chemical reactions. From molecular biology to biotechnology applications, computational …
chemical reactions. From molecular biology to biotechnology applications, computational …
Nonlinear ill-posed problem analysis in model-based parameter estimation and experimental design
T Barz, S Körkel, G Wozny - Computers & Chemical Engineering, 2015 - Elsevier
Discrete ill-posed problems are often encountered in engineering applications. Still, their
sound analysis is not yet common practice and difficulties arising in the determination of …
sound analysis is not yet common practice and difficulties arising in the determination of …