Autoregressive model fitting for control
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The use of a multidimensional extension of the minimum final prediction error (FPE) criterion which was originally developed for the decision of the order of one-dimensional autoregressive process  is discussed from the standpoint of controller design. It is shown by numerical examples that the criterion will also be useful for the decision of inclusion or exclusion of a variable into the model. Practical utility of the procedure was verified in the real controller design process of cement rotary kilns.
KeywordsController Design Autoregressive Model Manipulate Variable Prediction Error Variance liSr
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