Exact linearization of stochastic dynamical systems by state space coordinate transformation and feedback. I: -linearization.
Sládeček, Ladislav (2003)
Applied Mathematics E-Notes [electronic only]
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Sládeček, Ladislav (2003)
Applied Mathematics E-Notes [electronic only]
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Irina Bashkirtseva, Lev Ryashko (2013)
International Journal of Applied Mathematics and Computer Science
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A nonlinear discrete-time control system forced by stochastic disturbances is considered. We study the problem of synthesis of the regulator which stabilizes an equilibrium of the deterministic system and provides required scattering of random states near this equilibrium for the corresponding stochastic system. Our approach is based on the stochastic sensitivity functions technique. The necessary and important part of the examined control problem is an analysis of attainability. For...
Ljiljana Petrović (1983)
Publications de l'Institut Mathématique
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M. Métivier, J. Pellaumail (1977)
Publications mathématiques et informatique de Rennes
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J. Gani (1966-1967)
Publications mathématiques et informatique de Rennes
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M. Métivier, J. Pellaumail (1976)
Publications mathématiques et informatique de Rennes
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Michał Kisielewicz (1997)
Discussiones Mathematicae, Differential Inclusions, Control and Optimization
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The definition and some existence theorems for stochastic differential inclusions depending only on selections theorems are given.
Sridharan, V., Kalyani, T.V. (2005)
APPS. Applied Sciences
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Radovan Krtolica (1982)
Publications de l'Institut Mathématique
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Fabio Bagarello (2006)
Banach Center Publications
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Patrick Florchinger (2016)
Kybernetika
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In this paper we give sufficient conditions under which a nonlinear stochastic differential system without unforced dynamics is globally asymptotically stabilizable in probability via time-varying smooth feedback laws. The technique developed to design explicitly the time-varying stabilizers is based on the stochastic Lyapunov technique combined with the strategy used to construct bounded smooth stabilizing feedback laws for passive nonlinear stochastic differential systems. The interest...
Micha Kisielewicz (2003)
Discussiones Mathematicae, Differential Inclusions, Control and Optimization
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The Girsanov's theorem is useful as well in the general theory of stochastic analysis as well in its applications. We show here that it can be also applied to the theory of stochastic differential inclusions. In particular, we obtain some special properties of sets of weak solutions to some type of these inclusions.
Artstein, Zvi, Wets, Roger J.B. (1995)
Journal of Convex Analysis
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