Estimador estocástico para un sistema tipo caja negra

Abstract

This paper considers a black box system with unknown internal dynamics. The estimator based on instrumental variable requires, the transition matrix used in the identifier which results in a simplified model. The recursive space state model allows an explicit internal gain which is unknown and undescribed. The recursive estimator allows knowing the internal dynamics of the black box system in an analytic manner and in the best cases, converges to a reference neighborhood, becoming a necessary identification tool solving the convergence filter problem. The convergence estimator and the identifier are seen from the recursive functional identification error. An example was developed to simulate the DC motor in a finite differences model that requires knowing the operation of internal dynamics. The instrumental variable estimator describes the different operating condition parameters and monitors the direct current signal in finite differences. The functional error to different gains in the stability discrete region converges, and approximates the distribution of the direct current model.