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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 5/2018

29-09-2016 | Original Article

Study on neutral complex systems with Markovian switching and partly unknown transition rates

Authors: Xinghua Liu, Guoqi Ma, Hongsheng Xi

Published in: International Journal of Machine Learning and Cybernetics | Issue 5/2018

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Abstract

The exponential stability problem of uncertain neutral complex system with Markovian switching is investigated in the presence of nonlinear perturbations and partial information on transition rates. The study begins to consider the related nominal systems and construct a novel augmented stochastic Lyapunov functional which contains some triple-integral terms to reduce the conservatism. Then the exponential stability criteria are developed by utilizing Lyapunov stability theory, reciprocally convex lemma and free-weighting matrices. The results are further extended to the corresponding uncertain case. Finally, numerical examples are given to illustrate the effectiveness of the proposed methods.
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Appendix
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Metadata
Title
Study on neutral complex systems with Markovian switching and partly unknown transition rates
Authors
Xinghua Liu
Guoqi Ma
Hongsheng Xi
Publication date
29-09-2016
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 5/2018
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-016-0605-0

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