Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation

• Published in: Journal of the Franklin Institute Vol. 358; no. 9; pp. 5113 - 5135
• Main Authors: Ding, Feng, Ma, Hao, Pan, Jian, Yang, Erfu
• Format: Journal Article
• Language: English
• Published: Elmsford Elsevier Ltd 01.06.2021; Elsevier Science Ltd
• Subjects: Algorithms; Computer simulation; Errors; Hierarchies; Iterative algorithms; Iterative methods; Least squares; Mathematical models; Nonlinear equations; Nonlinear systems; Parameter identification; Parameterization; Separation; Subsystems
• ISSN: 0016-0032; 1879-2693; 0016-0032
• DOI: 10.1016/j.jfranklin.2021.04.006

This paper considers the parameter identification problems of the input nonlinear output-error (IN-OE) systems, that is the Hammerstein output-error systems. In order to overcome the excessive calculation amount of the over-parameterization method of the IN-OE systems. Through applying the hierarchial identification principle and decomposing the IN-OE system into three subsystems with a smaller number of parameters, we present the key term separation auxiliary model hierarchical gradient-based iterative algorithm and the key term separation auxiliary model hierarchical least squares-based iterative algorithm, which are called the key term separation auxiliary model three-stage gradient-based iterative algorithm and the key term separation auxiliary model three-stage least squares-based iterative algorithm. The comparison of the calculation amount and the simulation analysis indicate that the proposed algorithms are effective.