Performance analysis of the AM-SG parameter estimation for multivariable systems
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摘要
The auxiliary model based stochastic gradient (AM-SG) parameter estimation method is an important identification one. This paper analyzes the performances of the AM-SG estimation algorithm for multiple-input single-output systems (i.e., multivariable systems) under the strong persistent excitation condition. The analysis and simulation results indicate that the parameter estimation errors converge to zero.
论文关键词：Recursive identification,Parameter estimation,Stochastic gradient,Auxiliary models,Multivariable systems,Convergence properties
论文评审过程：Available online 17 December 2010.
论文官网地址：https://doi.org/10.1016/j.amc.2010.12.030
