Abstract
Identification for input nonlinear multivariable systems lies in that there exist the products of the parameters of the nonlinear block and the linear block. By means of the key-term separation principle, a subsystem least squares based iterative algorithm and a subsystem gradient based iterative algorithm are proposed for input nonlinear systems described by controlled autoregressive moving average models. Finally, the proposed methods are tested using numerical examples.
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