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Sampled‐parameter dependent stabilization for linear parameter varying systems with asynchronous parameter sampling
Author(s) -
Han Seungyong,
Lee Sangmoon
Publication year - 2021
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.5454
Subject(s) - parameterized complexity , control theory (sociology) , sampling (signal processing) , estimation theory , controller (irrigation) , distributed parameter system , model parameter , mathematics , linear matrix inequality , shape parameter , mathematical optimization , computer science , algorithm , statistics , control (management) , mathematical analysis , differential equation , filter (signal processing) , artificial intelligence , agronomy , computer vision , biology
In this paper, we propose a new sampled‐data stabilization method for linear parameter‐varying (LPV) systems with asynchronous parameter sampling. A sampled‐parameter‐dependent controller is designed by considering the sampling of parameters as well as that of states. Based on a newly proposed sampled‐parameter‐dependent looped‐functional (SPDLF), a relaxed linear matrix inequality (LMI) condition in the parameterized stabilization criteria is derived by considering the deviation bound between the continuous‐time parameter of the plant and the sampled parameter. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed method.