Stopping rules formation and faults detection in parametric identification problems

An approach to the generation of stopping rules in parametric identification problems is proposed on the basis of the computation of a statistic of the difference between two successive estimates. This statistic is also used for fault detection in the Kalman filter. The developed decision rules are applied to a linear system identification problem. Experimental results are presented to demonstrate the performance of the proposed algorithms.