MA 3 Process Data

One hundred simulations of a moving-average process were performed and the data recorded. The values are provided in Table 5.5. 

Sample time Value Sample time Value Sample time Value Sample time Value 

Modelling Dynamic Processes Using System Identification Methods 

Process system identification is a complex and involved process that can take on multiple different facets and requires understanding not mily the chemical and physical aspects of the process but also the mathematical and statistical background of identificaticm. In system identification, there are two basic approaches to this problem  

Data-driven or black-box modelling, where a description of the process is obtained solely by developing models for the available data. This approach can provide very accurate models of the system at a given set of conditions, but the model cannot generalise well to other conditions. Furthermore, developing such models can be difficult, since the selection of appropriate terms and relevant data is a nontrivial task. Unless the correlations are strong, it may be difficult to decide on an appropriate data-driven model. 

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Take the MA(3) process data in Sect. A5.3 and fit a MA(1) process to it. Analyse the residuals and fit. Comment on the results. Repeat, but using a MA(4) model. Compare the two models with the accurate MA(3) model (see Example 5.13 for the model). What happens when a model is over- or underfit ... 

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