Mean-square practical stability for uncertain stochastic system with additive noise controlled by optimal feedback

Stability concepts addressed in the framework of Lyapunov are not suitable to analyze the stability of stochastic systems with additive noise since it has no equilibrium. The mean-square practical stability is introduced to study the stability of uncertain stochastic systems with additive noise cont...

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Bibliographic Details
Published in:Optik (Stuttgart) 2016-07, Vol.127 (13), p.5334-5340
Main Authors: Mao, Dong-hui, Fang, Yang-wang, Yang, Peng-fei, Wu, You-li, Yong, Xiao-ju
Format: Article
Language:English
Subjects:
Additive noise
Additives
Control systems
Linear-quadratic optimal feedback
Lyapunov functional method
Mathematical models
Mean-square practical stability
Noise
Optimization
Stability
Stochastic systems
Uncertain stochastic system
Uncertainty
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Summary:Stability concepts addressed in the framework of Lyapunov are not suitable to analyze the stability of stochastic systems with additive noise since it has no equilibrium. The mean-square practical stability is introduced to study the stability of uncertain stochastic systems with additive noise controlled by linear-quadratic optimal feedback. By using Lyapunov functional methods and the comparison principle, criteria on mean-square practical stability of stochastic systems with partially known uncertainties and norm-bounded parameter uncertainties are deduced, respectively. Some numerical examples and simulations are given to illustrate the validity of the theoretical analysis.
ISSN:0030-4026
1618-1336
DOI:10.1016/j.ijleo.2016.02.068