A REFINED IV METHOD FOR CLOSED-LOOP SYSTEM IDENTIFICATION

Abstract This paper describes an optimal instrumental variable method for identifying discrete-time transfer function models of the Box-Jenkins transfer function form in the closed-loop situation. This method is based on the Refined Instrumental Variable (RIV) algorithm which, because of an appropriate choice of particular design variables, achieves minimum variance estimation of the model parameters. The Box-Jenkins model is the most natural since it does not constrain the process and the noise models to have common polynomials. The performance of the proposed approach is evaluated by Monte Carlo analysis in comparison with other alternative closed loop estimation methods.

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