Auxiliary Model-Based Multiple Innovation Recursive Algorithm on Nonlinear Systems utilizing KeyTerm Separation Technique
This article primarily investigates the identification problem for two-input one-output nonlinear controlled autoregressive moving average system. Drawing from the auxiliary model identification idea and the key-term separation technique, this article utilizes the estimated parameters to construct a...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Tamkang University Press
2025-02-01
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| Series: | Journal of Applied Science and Engineering |
| Subjects: | |
| Online Access: | http://jase.tku.edu.tw/articles/jase-202509-28-09-0010 |
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| Summary: | This article primarily investigates the identification problem for two-input one-output nonlinear controlled autoregressive moving average system. Drawing from the auxiliary model identification idea and the key-term separation technique, this article utilizes the estimated parameters to construct an auxiliary model. It then uses its outputs to replace the unknown terms and derives an auxiliary model-based recursive extended least-squares algorithm. For further improving the parameter estimation accuracy, an auxiliary model-based multi-innovation extended least-squares algorithm is presented by using the multi-innovation identification theory. Finally, a simulation example is demonstrated to verify the effectiveness of the derived algorithms. |
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| ISSN: | 2708-9967 2708-9975 |