Stubborn and Dead-Zone Redesign for Nonlinear Observers and Filters

• 成果类型: Article
• 署名作者: Astolfi, Daniele; Alessandri, Angelo; Zaccarian, Luca
• 署名单位: Universite Claude Bernard Lyon 1; Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Engineering & Systems Sciences (INSIS); University of Genoa; Universite de Toulouse; Centre National de la Recherche Scientifique (CNRS); University of Trento
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2020.2989816
• 发表日期: 2021
• 页码: 667-682
• 关键词: Dead-zone; input-to-state stability (ISS); nonlinear observers; saturation

摘要

We propose a redesign paradigm for stable estimators by introducing a saturation or a dead-zone nonlinearity with adaptive thresholds on the output injection term. Such nonlinearities allow improving the sensitivity to measurement noise in different scenarios (impulsive disturbances or persistent noise such as sensor bias), while preserving the asymptotic convergence properties of the original observer. These redesigns apply to a broad class of state estimators, including linear observers, observers for input-affine systems, observers for Lipschitz systems, observers based on the circle criterion, high-gain observers, standard and extended Kalman filters. Simulation results confirm the effectiveness of both the stubborn and dead-zone redesigns.