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Mean square exponential stabilization of sampled‐data Markovian jump systems
Author(s) -
Chen Guoliang,
Sun Jian,
Chen Jie
Publication year - 2018
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.4351
Subject(s) - mathematics , lyapunov function , exponential function , control theory (sociology) , exponential stability , interpolation (computer graphics) , exponential growth , square (algebra) , stability (learning theory) , computer science , mathematical analysis , nonlinear system , control (management) , animation , physics , computer graphics (images) , quantum mechanics , artificial intelligence , geometry , machine learning
Summary In this paper, the problem of mean square exponential stabilization for sampled‐data Markovin jump systems is studied. A time‐scheduled Lyapunov functional consisting of a exponential‐type looped function is constructed using segmentation technology and linear interpolation. Based on this new Lyapunov functional, a less conservative mean square exponential stability criterion is obtained such that a bigger maximum decay rate can be easily calculated. Meanwhile, the quantitative relationship among some system parameters, maximum sampling period, and decay rate is established. Moreover, a time‐dependent state feedback sample‐data controller is designed. Significant improvements of the proposed exponential‐type time‐scheduled Lyapunov functional method over some existing ones are verified by numerical examples.