Olga Granichina

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The problem of small UAVs flight optimization is considered. To solve this problem thermal updrafts are used. For the precise detection of the thermal updrafts center the simultaneous perturbation stochastic approximation (SPSA) type algorithm is proposed. If UAVs use thermal updrafts so they can save the energy during the flight. Therefore the flight time(More)
In this paper a distributed stochastic network system with incoming tasks that are classified with priorities is studied. The network system is assumed to have variable topology, and agents are not necessarily always connected to each other. In addition, the observations about neighbors' states are supposed to be obtained with random noise and delays. To(More)
In this paper, a new consensus problem, termed differentiated consensuses, is studied. This consensus problem is that, in a system with multiple classes, consensus is targeted for each class, which may be different among classes. Specifically, we investigate differentiated consensuses in a distributed stochastic network system of nodes (or agents), where(More)
This paper deals with a “differentiated consensuses” problem in a distributed stochastic network system with priorities. The network is considered as a set of heterogeneous agents that process incoming tasks with different importance (priority) levels. The observations about neighbors’ states are supposed to be obtained with random noise and delays and the(More)
In this paper we consider a possible application of simultaneous perturbation stochastic approximation (SPSA) method to problems of control of educational processes. SPSA is an efficient tool for optimization problems and uncertain parameters estimation. What is more important, such SPSA procedures actually work under arbitrary external observation noise,(More)
In this paper we join the previous results about asymptotic properties of a randomized control strategy with new one based on a non-asymptotic approach of LSCR (Leave-out Sign-dominant Correlation Regions) methods. Our consideration is focused on problems of the identification or adaptive optimal control for the linear plant with unknown parameters and(More)
The paper deals with the detection of abrupt changes in autonomous systems. We consider this problem in the presence of Gaussian noise and solve it in two steps. At first, spatial adaptive estimation of nonparametric regression is used to estimate the observable data. Then Filtered Derivative Algorithm is used to detect abrupt changes in the obtained data(More)