Auxiliary model-based stochastic gradient algorithm for multivariable output error systems

作者：Ding Feng^*; Liu Xiao Ping

来源：Acta Automatica Sinica, 2010, 36(7): 993-998.

DOI：10.3724/SP.J.1004.2010.00993

• Auxiliary models
• Convergence properties
• Martingale convergence theorem
• Recursive identification
• Stochastic gradient

The identification problem of multivariable output error systems is considered in this paper. By constructing an auxiliary model using available input-output data and by replacing the unknown inner variables in the information vector with the outputs of the auxiliary model, an auxiliary model-based stochastic gradient (AM-SG) identification algorithm is presented. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates given by the AM-SG algorithm converge to their true values. The AM-SG algorithm with a forgetting factor is given to improve its convergence rate. The simulation results confirm the theoretical findings.

• 出版日期2010
• 单位江南大学