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)
In this paper the randomized stochastic approximation (RSA) methods for optimization problems for system unknown parameters tracking are studied. Such randomized SA procedures are working under arbitrary external observation noise. One of the possible application of the method to a control of educational processes is presented.
This paper deals with a “differentiated consensuses” problem in a distributed stochastic network system with priorities and cost constraints on system topology. 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(More)
— Multidimensional stochastic optimization plays an important role in analysis and control of many technical systems. To solve the challenging problems of multidimensional optimization, it was suggested to use the randomized algorithms of stochastic approximation with perturbed input which have simple forms and provide consistent estimates of the unknown(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)
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