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Novel data filtering based parameter identification for multiple-input multiple-output systems using the auxiliary model
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DOI：10.1016/j.automatica.2016.05.024.png)
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This communique uses the auxiliary model method to study the identification problem of a multiple input multiple-output (MIMO) system. For such a MIMO system whose outputs are contaminated by an ARMA noise process (i.e., correlated noise), an auxiliary model based recursive least squares parameter estimation algorithm is presented through filtering input-output data. The proposed algorithm has higher estimation accuracy than the existing multivariable identification algorithm. The simulation example is given. (C) 2016 Elsevier Ltd. All rights reserved.
Keyword:
Recursive identification
Least squares
Auxiliary model
Hierarchical identification
MIMO system
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期刊
IF:
5.9
论文数:
1.2W
被引数:
5.2W
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