Analytical Identification of Polynomial Nonlinear Systems With Uncontrollable Linearization

• 成果类型: Article
• 署名作者: Huang, Chao; Zhang, Hao; Wang, Zhuping
• 署名单位: Tongji University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3577068
• 发表日期: 2025
• 关键词: domain

摘要

Recently, system identification (SID) based on center manifold (CM) is proposed to identify polynomial nonlinear systems (PNSs) analytically. With this method, estimating the unknown parameters in the PNSs is converted to the problem of solving a set of recursively defined Sylvester equations (RSEs). However, the existing CM-based SID algorithm assumes the linearization of the PNS to be controllable. In this note, we propose a more general framework that allows for uncontrollable linearizations. By a new formulation of the RSEs, it is shown that controllability can be attained in the high-order RSEs, so that the frequency-domain subspace SID method can be invoked to identify all the parameters in the PNS. Consistency is proved if a set of persistence of excitation conditions is satisfied.