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Abstract
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.
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