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State feedback stabilization of stochastic nonlinear systems with SiISS inverse dynamics
Author(s) -
Duan Na,
Xie XueJun,
Yu Xin
Publication year - 2011
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.1677
Subject(s) - control theory (sociology) , nonlinear system , inverse dynamics , inverse , state (computer science) , bounded function , stability (learning theory) , controller (irrigation) , computer science , feedback controller , mathematics , control (management) , algorithm , mathematical analysis , physics , geometry , kinematics , classical mechanics , quantum mechanics , artificial intelligence , machine learning , agronomy , biology
This paper further considers a more general class of stochastic nonlinear systems with stochastic integral input‐to‐state stability (SiISS) inverse dynamics and drift and diffusion terms depending upon the other states besides stochastic inverse dynamics and the first state. By skillfully choosing the designed functions and the update laws of parameters, and using the important mathematical tools established in IEEE Trans. Automat. Contr. 2010; 55 (2):304–320, a unifying framework of state feedback controller is proposed to guarantee that all the signals of the closed‐loop system are bounded almost surely and the states can be regulated to zero almost surely. A simulation example demonstrates the effectiveness of the control scheme. Copyright © 2011 John Wiley & Sons, Ltd.