Abstract
In many industrial cases it is not feasible to measure primary outputs, e.g. product quality, from production processes on-line. It is thus of interest to estimate such outputs from known process inputs and secondary process measurements. In an earlier paper it is shown that optimal estimators can be identified from data recorded during an informative experiment, with the primary outputs sampled at the same high rate as the inputs and secondary outputs. In the present paper it is shown that optimal estimators can also be found from data where the primary outputs are sampled at a low and possibly irregular rate.
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