Auxiliary Model-Based Multiple Innovation Recursive Algorithm on Nonlinear Systems utilizing KeyTerm Separation Technique

Fang  Qiu; Yan  Ji

doi:10.6180/jase.202509_28(9).0010

Auxiliary Model-Based Multiple Innovation Recursive Algorithm on Nonlinear Systems utilizing KeyTerm Separation Technique

Aerospace Engineering

Fang QiuThis email address is being protected from spambots. You need JavaScript enabled to view it. and Yan Ji

College of Science, Shandong University of Aeronautics, Binzhou 256600, China

Received: August 8, 2023
Accepted: October 24, 2024
Publication Date: December 28, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202509_28(9).0010

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.

Keywords: Recursive identification, Auxiliary model, Multi-innovation identification, Parameter estimation

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