Identificador con comparación entre dos estimadores
Keywords:
Computer modeling, simulation, algorithms for functional approximation, stochastic processes, fuzzy logic, artificial intelligenceAbstract
This paper describes the identification process as an adaptive digital filter using the estimated transition matrix, identification error and gain functions. One problem that the filter has is the time process, affecting the quality response and agreeing with the estimated transition function, which is a condition to be accomplished with respect to the reference time evolution system. Thus, the time process required must be met in all operations within the same time interval. Generally, the identifier filter answer is affected by the parameter used in the estimated transition function indirectly used in the other filter operations. In this case, seeking a better time estimation response two estimators were considered: the first expressed in a recursive form and the second, selected within the knowledge base gain used in accordance to fuzzy logic. The results show the convergence observed in the error differences and their approximations to the stochastic time model conditions with $k$ samples, using, MatLab$^{\mbox{\textregistered }}$ as a simulation software.Downloads
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Authors retain copyright and grant the Revista Mexicana de Física right of first publication with the work simultaneously licensed under a CC BY-NC-ND 4.0 that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.