Object
Title: Issues in nonlinear parameter estimation and multivariate model discrimination: Applications in polymer reaction engineering
Contributor:
Skliar, Mikhail - red. ; Ramirez, W. Fred - red.
Subtitle:
Data Processing and Process Control
Group publication title:
Abstract:
In this paper an overview is given of issues in parameter estimation, model discrimination, and optimal sensor selection as they relate to the modelling of copolymerization processes. The problems are discussed in the context of a comprehensive polymerization simulation package that is being developed, which includes an extensive database. A brief description of the modelling equations together with a listing of equations used to predict copolymer composition, triad fractions and polymerization rate, which are the primary responses used throughout this paper, is given. ; The problem of reactivity ratio estimation is reviewed and a method based on the Error-in-Variables model (EVM) is described which has the advantage that it properly accounts for all the errors in the measurements being used in the estimation. Two methods for describing the uncertainty in the estimates obtained are given. The first establishes approximate elliptical contours which are approximate in both shape and size. ; The other approach offers an improvement in that contours having the correct shape are calculated. The problem of discriminating between two models based on the terminal and penultimate mechanism using the method proposed by Buzzi-Ferraris and Forzatti (1983) is described. Simulations using copolymer composition, triad fractions and copolymerization rate are compared. ; An experimental verification for styrene/methyl methacrylate and triad fraction data is discussed and contrasted with previous experimental results. A comparison between experiments designed using the model discrimination criterion and those using equally-spaced points shows that in general the designed experiments are better able to correctly discriminate. Furthermore, even in those cases when the equally-spaced experiments lead to correct model discrimination, they usually lead to poor estimates of the model prediction error and the parameter uncertainty. ; Finally, the problem of optimally selecting sensors for a polymerization process is discussed. The approach shown uses a Kalman filter to optimally combine the polymerization model with process data. The different sensor scenarios are ranked using the determinant of the state covariance matrix.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Resource Identifier:
Pages:
Source:
AMCS, volume 8, number 4 (1998) ; click here to follow the link
Language:
Rights:
Biblioteka Uniwersytetu Zielonogórskiego
Object collections:
- Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Repository > Types of work > Articles
- Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS)
- Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (1998)
Last modified:
Sep 3, 2021
In our library since:
Dec 22, 2020
Number of object content hits:
51
All available object's versions:
https://zbc.uz.zgora.pl/repozytorium/publication/64677
Show description in RDF format:
Show description in OAI-PMH format:
-
International Journal of Applied Mathematics and Computer Science (AMCS)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 25 (2015)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 24 (2014)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 23 (2013)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 22 (2012)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 21 (2011)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 20 (2010)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 19 (2009)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 18 (2008)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 17 (2007)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 16 (2006)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 15 (2005)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 13 (2003)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 12 (2002)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 11 (2001)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 10 (2000)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 9 (1999)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 8 (1998)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 8, number 1 (1998)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 8, number 2 (1998)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 8, number 3 (1998)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 8, number 4 (1998)
- The implicit daisy-chaining property of constrained predictive control
- Distributed output feedback control of two-time-scale hyperbolic PDE systems
- Source identification in distributed parameter systems
- The Heisenberg modelling procedure and applications to process control
- Contribution plots: A missing link in multivariate quality control
- Nonlinear black-box identification of distillation column models - design variable selection for model performance enhancement
- Issues in nonlinear parameter estimation and multivariate model discrimination: Applications in polymer reaction engineering
- Lake bed classification using acoustic data
- Neural network signal interpretation for optimization of chromatographic protein purifications
- System modelling using neural network parameter functions
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 8, number 1 (1998)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 7 (1997)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 6 (1996)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 5 (1995)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 4 (1994)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 3 (1993)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 2 (1992)
-
International Journal of Applied Mathematics and Computer Science (AMCS),volume 1 (1991)
-
International Journal of Applied Mathematics and Computer Science (AMCS), volume 26 (2016)
