Recursive estimation methods for discrete systems

In system identification, the error evolution is composed of two decoupled parts: one is the identifying information on the current estimation residual, while the other is past arithmetic errors. Previous recursive algorithms only considered how to update current prediction errors. Up to now, research has mostly been based on recursive least-squares (RLS) methods. In this note, a general recursive identification method is proposed for discrete systems. Using this new algorithm, a recursive empirical frequency-domain optimal parameter (REFOP) estimate is established. The REFOP method has the advantage of resisting disturbance noise. Some simulations are included to illustrate the new method's reliability.