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Parameter Identification for Input Nonlinear Output-Error Systems Using the Unknown Variable Estimation

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2 Author(s)

The information vector in the identification model obtained by parameterizing input nonlinear systems contains unknown variables - the noise-free (true) outputs of the system. This is the difficulty of identification. This paper develops a stochastic gradient based identification algorithm by replacing the unknown variable with its estimate. The simulation results show the effectiveness of the proposed algorithms.

Published in:

American Control Conference, 2007. ACC '07

Date of Conference:

9-13 July 2007