Estimador para un Proceso Estocástico de Tercer Orden

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This paper presents the estimation considering the Second Probability Moment applied to a simplified Third Order Stochastic Process. Model commonly used to describe smoothing systems as a synchronous motor. Its values used into the model describe and estimate the Black Box system behavior. In the design three parameters based on covariance P k and Q k are calculated The stochastic variable depends on the three gains and three functional estimation errors, respectively, developing the stochastic identification by a reference model that converges in almost all points with 10 iterations in recursive estimation. The results demonstrate a theoretical experiment using the Matlab obtaining the parameters and the third order model to converge in accordance to the reference signal. The accuracy achieved in thousandths was in a Supermartingale sense and implementation performed as a function of recursive estimation




Medel, J. J., Urbieta, P. R., & García, I. J. C. (2014). Estimador para un Proceso Estocástico de Tercer Orden. RIAI - Revista Iberoamericana de Automatica e Informatica Industrial, 11(4), 389–394.

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