Extended Global Total Least Square Approach to Multiple-model Identification
نویسندگان
چکیده
The paper proposes a novel global total least square procedure which has been appropriately extended for multiple-model identification of nonlinear systems. The resulting scheme which is a hybrid iterative procedure, makes repeated use of both the behavioural and classical approaches. Model parameters are optimised in order to minimise the distance between an observed time series and the simulated time series of the resulting optimised behavioural model. The developed procedure is demonstrated when applied to an arbitrary nonlinear system. Copyright c ©2005 IFAC
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