Robust Parameter Estimation in Nonlinear Dynamic Process Models
نویسندگان
چکیده
Parameter estimation is a key issue in the mathematical modelling of nonlinear dynamic processes. Standard (gradient-based) methods for data fitting in nonlinear dynamic systems can suffer from slow and/or local convergence, among other problems. However, this is frequently ignored, potentially leading to wrong conclusions about the validity of a model regarding a certain data set. In order to surmount these difficulties, we present alternative methods based on global optimisation and identifiability analysis.
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تاریخ انتشار 2005