CORRECTION FOR DRIFT IN MULTIVARIATE SYSTEMS USING THE KALMAN FILTER

Many analytical instruments can now be used effectively to monitor ind ustrial and environmental processes on-line. In the large majority of cases, however, the instrument must be first calibrated, and then reca librated if the instrument characteristics change with time. Here an a pproach for detection and correct:on of time-dependent drift in multiv ariate calibration parameters is described. Kalman filters can be devi sed that correct for drift in the baseline and drift in sensitivities, either through purely random processes, or a combination of linear an d random drift. Some examples of implementations of this filter are de monstrated using synthetic, near-infrared, and UV-visible spectrophoto metric data. The application of the Kalman filter to the inverse calib ration problem is also demonstrated.