Estimation of reaction rates by nonlinear system inversion

Abstract:
The estimation of reaction rates is an important problem in mechanistic modeling, monitoring and control of chemical reactors. In contrast to standard estimation techniques where a model must be chosen for the reaction rates, we consider them in this work as unknown time-varying functions, which also may be interpreted as inputs. The resulting estimation task is an ill-posed inverse problem. The paper addresses this estimation problem based on systematic methods for nonlinear system inversion and filtering resulting in efficient estimators. A theoretical analysis reveals the conditions for reaction rate reconstruction are those for system invertibility. Our estimation scheme is a regularization method which eliminates the difficulties arising with ill-posed problems. Guidelines for the design of the estimator structure and the selection of the regularization parameters are presented.

Keywords:
Inverse problems, ill-posed problems, system inversion, filtering, regularization, reaction rates.

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