Highly-computational hierarchical iterative identification methods for multiple-input multiple-output systems by using the auxiliary models

The identification of multiple-input multiple-output (MIMO) systems is an important part of designing complex control systems. This article studies an auxiliary model least squares iterative (AM-LSI) algorithm for MIMO systems. With the expansion of the system scale and limitations of the computer resources, there is an urgent need for an identification algorithm that provides higher computational efficiency. To address this issue, this article further derives a hierarchical identification model and proposes a new auxiliary model hierarchical least squares iterative (AM-HLSI) algorithm for MIMO systems by applying the hierarchical identification principle. Through the analysis of the computational efficiency, the AM-HLSI algorithm has higher computational efficiency than the AM-LSI algorithm. Additionally, the feasibility of the AM-LSI and AM-HLSI algorithms is validated by a simulation example.