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Robust stabilization of hybrid uncertain stochastic systems by discrete‐time feedback control
Author(s) -
Li Yuyuan,
Lu Jianqiu,
Kou Chunhai,
Mao Xuerong,
Pan Jiafeng
Publication year - 2016
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2293
Subject(s) - control theory (sociology) , stochastic differential equation , discrete time and continuous time , feedback control , bounded function , mathematics , differential (mechanical device) , control (management) , state (computer science) , norm (philosophy) , matrix (chemical analysis) , stochastic control , mean square , computer science , mathematical optimization , optimal control , engineering , control engineering , mathematical analysis , algorithm , statistics , law , artificial intelligence , political science , aerospace engineering , materials science , composite material
Summary This paper aims to stabilize hybrid stochastic differential equations with norm‐bounded uncertainties by feedback controls based on the discrete‐time observations of both state and mode. The control structure appears only in the drift part (the deterministic part) of a stochastic differential equations, and the controlled system will be robustly exponentially stable in mean square. Our stabilization criteria are in terms of linear matrix inequalities whence the feedback controls can be designed more easily in practice. An example is given to illustrate the effectiveness of our results. Copyright © 2016 John Wiley & Sons, Ltd.