Highly-efficient coupled recursive least squares identification algorithm for multivariable systems and its computational amount analysis
JIN Yu
ZHANG Xiao
DING Feng
Abstract：Because of the a large-scale multivariable system has a large number of parameters and its identification algorithms require a large amount of computation,a highly-efficient coupled recursive least squares algorithm is derived for a multivariable system based on the coupling identification concept.The main idea of the algorithm is to couple the same parameter vectors among subsystems according to the characteristics of each subsystem identification model,so as to avoid the redundant estimation of the subsystem parameter vectors.The computational efficiency analysis shows that the proposed algorithm has less amount of computation than the recursive least squares algorithm.The simulation example verifies the effectiveness of the proposed algorithm.
Keywords：parameter estimationcoupling identification conceptrecursive identificationleast squaresmultivariable systems
Publication Date：2025-02-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 364-372 )