A protocol for the estimation of parameters in process models

As our understanding of chemical processes increases the models created to describe them also increase in complexity. These models usually consist of sets of differential equations, containing multiple response variables which are a function of multiple input or design variables and a potentially large number of parameters. To be able to use these models effectively the parameters that they contain have to be known.; At present in estimating parameters for large process models, there are two shortcomings in the existing knowledge about parameter estimation. The first is, how effective is the present parameter estimation methodology when applied to large models, and the second is, can any advantage be gained from considering the parameter estimation problem as a whole. This work will try to address this limitation, by revisiting the parameter estimation process and developing a protocol for the estimation or updating of the parameters within process models.; The projected use of the parameter estimation protocol is as part of a model based experimentation program. Therefore it considers actual experimental conditions, where the number of experiments that can be carried out is limited due to the expense of performing experiments and analysis.; In the development of a parameter estimation protocol all of the steps of the parameter estimation will be revisited. The parameter estimation steps are: parameter sensitivity analysis, statistical design of experiments, estimation of parameters and confidence regions. Where these four steps correspond to answering the following questions; (1) Is it possible to estimate the parameters with the chosen responses and which response or responses will provide the most information? (2) At what conditions (i.e. temperature, conversion, initial feed composition) should the data in the experiment be collected? (3) What is the best method to estimate the parameters with the data that was collected? (4) How good are the parameters that were estimated?; Of the parameter sensitivity analysis methods available it was found that the best method to present sensitivity information is a plot of the gradient values of the responses with respect to the parameters. (Abstract shortened by UMI.)...