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Adaptive control of stochastic nonlinear systems with Markovian switching
Author(s) -
Wang G.L.,
Zhang Q.L.
Publication year - 2012
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2275
Subject(s) - control theory (sociology) , nonlinear system , adaptive control , markov process , bounded function , controller (irrigation) , class (philosophy) , mathematics , state (computer science) , computer science , control (management) , algorithm , physics , mathematical analysis , statistics , quantum mechanics , artificial intelligence , agronomy , biology
SUMMARY This paper is concerned with the problem of adaptive control for a class of stochastic nonlinear systems with Markovian switching, where the upper bounds of nonlinearities of stochastic Markovian jump systems are assumed to be unknown. Firstly, an adaptation law is developed to estimate these unknown parameters. Then, a class of adaptive state feedback controller is proposed such that not only the estimated errors are bounded almost surely but also, the states of the resulting closed‐loop system are asymptotically stable almost surely. Finally, a numerical example is given to show the validity of the results.Copyright © 2012 John Wiley & Sons, Ltd.