- Autor(i):
- M. Čižniar – M. Podmajerský – T. Hirmajer – M. Fikar – M. A. Latifi
- Názov:
- Global optimization for parameter estimation of differential-algebraic systems
- Časopis:
- Chemical Papers
- Rok:
- 2009
- Kľúčové slovo(á):
- identifikácia parametrov, ortogonálna kolokácia, dynamická optimalizácia, globálna optimalizácia
- Zväzok:
- 63
- Číslo:
- 3
- Strany:
- 274–283
- Jazyk:
- angličtina
- Anotácia:
The estimation of parameters in semi-empirical models is essential in numerous areas of engineer- ing and applied science. In many cases, these models are described by a set of ordinary-diﬀerential equations or by a set of diﬀerential-algebraic equations. Due to the presence of non-convexities of functions participating in these equations, current gradient-based optimization methods can guarantee only locally optimal solutions. This deﬁciency can have a marked impact on the operation of chemical processes from the economical, environmental and safety points of view and it thus motivates the development of global optimization algorithms. This paper presents a global optimization method which guarantees ε-convergence to the global solution. The approach consists in the transformation of the dynamic optimization problem into a nonlinear programming problem (NLP) using the method of orthogonal collocation on ﬁnite elements. Rigorous convex underestimators of the nonconvex NLP problem are employed within the spatial branch-and-bound method and solved to global optimality. The proposed method was applied to two example problems dealing with parameter estimation from time series data.

- ISSN:
- 0366-6352
- Kategória publikácie:
- ADD – Vedecké práce v domácich karentovaných časopisoch
- Oddelenie:
- OIaRP
- Vložil/Upravil:
- Ing. Michal Čižniar
- Posledná úprava:
- 28.3.2009 19:16:19
- Plný text:
- Plný text nie je prístupný verejnosti, ale môžete požiadať o kópiu niektorého z autorov
- BibTeX:
- @article{uiam788,
author = {M. {\v{C}}i\v{z}niar and M. Podmajersk\'y and T. Hirmajer and M. Fikar and M. A. Latifi}, title = {Global optimization for parameter estimation of differential-algebraic systems}, journal = {Chemical Papers}, year = {2009}, keyword = {identifik\'acia parametrov, ortogon\'alna kolok\'acia, dynamick\'a optimaliz\'acia, glob\'alna optimaliz\'acia}, volume = {63}, number = {3}, pages = {274-283}, annote = {The estimation of parameters in semi-empirical models is essential in numerous areas of engineer- ing and applied science. In many cases, these models are described by a set of ordinary-diﬀerential equations or by a set of diﬀerential-algebraic equations. Due to the presence of non-convexities of functions participating in these equations, current gradient-based optimization methods can guarantee only locally optimal solutions. This deﬁciency can have a marked impact on the operation of chemical processes from the economical, environmental and safety points of view and it thus motivates the development of global optimization algorithms. This paper presents a global optimization method which guarantees ε-convergence to the global solution. The approach consists in the transformation of the dynamic optimization problem into a nonlinear programming problem (NLP) using the method of orthogonal collocation on ﬁnite elements. Rigorous convex underestimators of the nonconvex NLP problem are employed within the spatial branch-and-bound method and solved to global optimality. The proposed method was applied to two example problems dealing with parameter estimation from time series data. }, url = {https://www.uiam.sk/assets/publication_info.php?id_pub=788}