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Hierarchical Recursive Least Squares Estimation Algorithm for Second-order Volterra Nonlinear Systems

Jian Pan*, Sunde Liu, Jun Shu, and Xiangkui Wan
International Journal of Control, Automation, and Systems, vol. 20, no. 12, pp.3940-3950, 2022

Abstract : This paper considers the parameter identification problems of a Volterra nonlinear system. In order to overcome the excessive calculation amount of the Volterra systems, a hierarchical least squares algorithm is proposed through combining the hierarchical identification principle. The key is to decompose the Volterra systems into three subsystems with a smaller number of parameters and to estimates the parameters of each subsystem, respectively. The calculation analysis indicates that the proposed algorithm has less computational cost than the recursive least squares algorithm. Finally, the simulation results indicate that the proposed algorithm are effective for identifying Volterra systems.

Keyword : Hierarchical identification, nonlinear system, parameter identification, recursive least squares, Volterra system.

 
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