Recursive Algorithms for Multivariable Output-Error-Like ARMA Systems

• Main Authors: Hao Ma, Jian Pan, Lei Lv, Guanghui Xu, Feng Ding, Ahmed Alsaedi, Tasawar Hayat
• Format: Article
• Language: English
• Published: MDPI AG 2019-06-01
• Series: Mathematics
• Subjects: system identification; recursive algorithm; least squares; multivariable system; coupling identification concept
• Online Access: https://www.mdpi.com/2227-7390/7/6/558

This paper studies the parameter identification problems for multivariable output-error-like systems with colored noises. Based on the hierarchical identification principle, the original system is decomposed into several subsystems. However, each subsystem contains the same parameter vector, which leads to redundant computation. By taking the average of the parameter estimation vectors of each subsystem, a partially-coupled subsystem recursive generalized extended least squares (PC-S-RGELS) algorithm is presented to cut down the redundant parameter estimates. Furthermore, a partially-coupled recursive generalized extended least squares (PC-RGELS) algorithm is presented to further reduce the computational cost and the redundant estimates by using the coupling identification concept. Finally, an example indicates the effectiveness of the derived algorithms.