A High-Order Sliding-Mode Adaptive Observer for Uncertain Nonlinear Systems

• 成果类型: Article
• 署名作者: Rios, Hector; Franco, Roberto; Ferreira de Loza, Alejandra; Efimov, Denis
• 署名单位: Consejo Nacional de Ciencia y Tecnologia (CONACyT); Instituto Politecnico Nacional - Mexico; Inria; Universite de Lille; Centre National de la Recherche Scientifique (CNRS)
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2021.3139308
• 发表日期: 2023
• 页码: 408-415
• 关键词: Adaptive observers; Nonlinear systems; sliding-modes

摘要

A high-order sliding-mode adaptive observer is proposed to solve the problem of an adaptive estimation, i.e., the simultaneous estimation of the state and parameters, for a class of uncertain nonlinear systems in the presence of external disturbances, which do not need to satisfy a relative degree condition equal to one. This approach is based on a high-order sliding-mode observer and a nonlinear parameter identification algorithm. The practical, global, and uniform asymptotic stability of the adaptive estimation error, despite the external disturbances, is guaranteed through the small-gain theorem. The convergence proofs are developed based on the Lyapunov and input-to-state stability theories. Some simulation results illustrate the performance of the proposed high-order sliding-mode adaptive observer.