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Global sampled‐data output‐feedback stabilization for nonlinear systems with unknown measurement sensitivity
Author(s) -
Wang Pan,
Chai Lin,
Chen ChihChiang,
Fei Shumin
Publication year - 2019
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.4668
Subject(s) - control theory (sociology) , sensitivity (control systems) , nonlinear system , novelty , output feedback , observer (physics) , feedback control , nonlinear control , sampling (signal processing) , computer science , control (management) , mathematics , control engineering , engineering , artificial intelligence , philosophy , physics , theology , filter (signal processing) , quantum mechanics , electronic engineering , computer vision
Summary This paper investigates the problem of global output‐feedback stabilization by sampled‐data control for nonlinear systems with unknown measurement sensitivity. By employing the technique of output‐feedback domination, a sampled‐data output‐feedback control law together with a sampled‐data state observer is explicitly constructed. By an exquisite selection of both the domination gain and sampling period, the resultant control law is a globally asymptotic stabilizer even in the presence of unknown measurement sensitivity. The novelty of this paper is the development of a distinct approach which can tackle the problem of output‐feedback stabilization for the nonlinear systems with unknown measurement sensitivity.