Control-Enabling Adaptive Nonlinear System Identification

• 成果类型: Article
• 署名作者: Zisis, Konstantinos; Bechlioulis, Charalampos P.; Rovithakis, George A.
• 署名单位: Aristotle University of Thessaloniki; University of Patras
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3106870
• 发表日期: 2022
• 页码: 3715-3721
• 关键词: Adaptive systems; trajectory; nonlinear dynamical systems; Mathematical model; Linear systems; uncertainty; transient analysis; Adaptive identification; persistency of excitation (PE)

摘要

In this article, we rely on the theoretical foundations of radial basis function neural networks to form an adaptive parameter estimation problem, which we solve using the recently introduced prescribed performance control methodology. Such combination results in a compact user-configurable adaptive nonlinear system identification methodology that can be used to retrieve the open-loop nonlinear plant dynamics in any compact region of interest.