Год издания: 2006
Количество страниц: 351
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In process modelling, knowledge of the process under consideration is typically partial with significant unknown inputs (disturbances) to the model. Disturbances militate against the desirable trait of model reproducibility. "Grey-box" identification can assist, in these circumstances, by taking advantage of the two sources of information that may be available: any invariant prior knowledge and response data from experiments. Practical Grey-box Process Identification is a three-stranded response to the following questions which are frequently raised in connection with grey-box methods: How much of my prior knowledge is useful and even correct in this environment? Are my experimental data sufficient and relevant? What do I do about the disturbances that I can’t get rid of? How do I know when my model is good enough? The first part of the book is a short review of the theoretical fundamentals of grey-box...