On primary output estimation by use of secondary measurements as input signals in system identification

摘要

In many cases, vital output variables in, e.g., industrial processes cannot be measured online. It is then of interest to estimate these primary variables from manipulated and measured inputs and the secondary output measurements that are available. In order to identify an optimal estimator from input-output data, a suitable model structure must be chosen. The paper compares use of ARMAX and output error (OE) structures in prediction error identification methods, theoretically and through simulations.