(89b) Global Optimization for Parameter Estimation in Dynamic Systems | AIChE

(89b) Global Optimization for Parameter Estimation in Dynamic Systems

Authors 

Lin, Y. - Presenter, University of Notre Dame


Parameter estimation is a key step in the development of mathematical models of physical phenomena, and is well studied [1]. In many problems, especially in chemical engineering, the systems are nonlinear in nature and described by ordinary differential equations (ODEs), or by differential-algebraic equations (DAEs). These factors lead to the important issue of multiplicity of local solutions in the parameter estimation [2,3].

In this study, we present a deterministic global optimization approach for parameter estimation in dynamic systems. The approach is based on an interval-Newton approach [4,5]. Validated solution methods [6-8] for ODEs (initial value problems) are used to produce bounds that are guaranteed to contain the true solutions of a dynamic system with uncertainty in parameters, as well as the first- and second-order sensitivities of the states with respect to parameters. Computational details and results will be presented through application to several problems involving reaction kinetics.

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