Partially coupled gradient-based iterative identification methods for multivariable output-error moving average systems

This paper focuses on the identification problems of multivariable output-error moving average systems and develops a partially coupled gradient-based iterative algorithm to estimate the parameters of the systems. The key is combining the hierarchical identification principle and the coupling identification concept to decompose a multivariable system into m subsystems (m is the number of outputs), and then to identify the subsystems one by one. Compared with the gradient-based iterative algorithm, the partially coupled gradient-based iterative algorithm requires less computational efforts. The simulation results show that the proposed algorithms are effective.