On Robust Observer Design for a Class of Time-Varying Continuous-Time and Discrete-Time Persidskii Systems

• 成果类型: Article
• 署名作者: Khalin, Anatolii; Efimov, Denis; Ushirobira, Rosane
• 署名单位: Universite de Lille; Centre National de la Recherche Scientifique (CNRS); Inria
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2023.3333791
• 发表日期: 2024
• 页码: 2660-2667
• 关键词: Observers; MANIFOLDS; Time-varying systems; stability analysis; Nonlinear systems; CONVERGENCE; trajectory; Lyapunov methods; observers; steady-state

摘要

This article considers the state estimation problem for a class of nonautonomous nonlinear systems. We propose conditions on the existence and stability of a nonlinear observer based on the invariant manifold approach in both continuous- and discrete-time scenarios. The requirements are formulated using linear matrix equalities (LME) and inequalities (LMI). We present two possible applications of the result, a reduced-order observer (e.g., an observer for unmeasured states) and regression in linear and nonlinear, continuous- and discrete-time settings. With nonlinear regression being a sophisticated case, the parameter estimation problem for a particular output equation (when the fusion of linear and nonlinear sensors is weighted) is investigated. Two nonlinear examples demonstrating the efficiency of results are provided.