Coupled Least Squares Identification Algorithms for Multivariate Output-Error Systems

• Main Authors: Wu Huang, Feng Ding
• Format: Article
• Language: English
• Published: MDPI AG 2017-01-01
• Series: Algorithms
• Subjects: coupling identification concept; parameter estimation; auxiliary model; least squares; multivariate system
• Online Access: http://www.mdpi.com/1999-4893/10/1/12

This paper focuses on the recursive identification problems for a multivariate output-error system. By decomposing the system into several subsystems and by forming a coupled relationship between the parameter estimation vectors of the subsystems, two coupled auxiliary model based recursive least squares (RLS) algorithms are presented. Moreover, in contrast to the auxiliary model based recursive least squares algorithm, the proposed algorithms provide a reference to improve the identification accuracy of the multivariate output-error system. The simulation results confirm the effectiveness of the proposed algorithms.