Issues in Closed-loop Identiication
نویسندگان
چکیده
In this contribution we study the statistical properties of a number of closed-loop identiication methods and parameterizations. A focus will be on asymptotic variance expressions for these methods. By studying the asymptotic variance for the parameter vector estimates we show that indirect methods fail to give better accuracy than the direct method. Some new results for bias distribution in closed-loop experiments will also be presented. It is also shown how diierent methods correspond to diierent parameterizations and how direct and indirect identiication can be linked together via the noise model.
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