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Robust sampled‐data controller design for uncertain nonlinear systems via Euler discretization
Author(s) -
Coutinho Pedro H.S.,
Bernal Miguel,
Palhares Reinaldo M.
Publication year - 2020
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.5234
Subject(s) - discretization , control theory (sociology) , parametric statistics , nonlinear system , bounded function , controller (irrigation) , mathematics , euler's formula , robust control , discrete time and continuous time , computer science , class (philosophy) , mathematical optimization , control (management) , mathematical analysis , artificial intelligence , physics , quantum mechanics , agronomy , biology , statistics
Summary Robust stabilization of a class of uncertain nonlinear systems through a sampled‐data control law is considered in this work. Based on the forward discrete‐time Euler approximation, conditions in the form of linear matrix inequalities are provided to synthesize a discrete controller that guarantees the states to be asymptotically driven to the origin, regardless of the presence of bounded parametric uncertainties. In contrast with other approaches, the system is not required to be Lure‐type nor the conditions to have predefined gains to be tested. Examples are given to illustrate the effectiveness of the proposal.