System identification by ARMA modeling
Dal Santo, Paul S.
Ziomek, Lawrence J.
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System identification concerns the mathematical modeling of a system based upon its input and output. It allows the development of a mathematical description when all that is available is the result of a process or the output of a system and not the process or system itself. The purpose of this thesis is to develop algorithms for modeling systems as autoregressive-moving-average processes using the method of instrumental variables, a modification of the ordinary least-squares technique, and a multichannel method based upon processing the input and output data by separate infinite-response filters. The methods developed are tested by computer simulation using several second and third-order test cases and the results are presented
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