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Distributed State Estimation of Moving Targets Using Cyclic simultaneous perturbation stochastic approximation

IFAC-PapersOnLine 2018年第23期51卷 218-223页

作者： Erofeeva, Victoria Granichin, Oleg Institute of Problems in Mechanical Engineering Russian Academy of Sciences Saint Petersburg Russia

Sensor networks comprised of multiple nodes with sensing, processing and communication capabilities are ubiquitous in tracking systems. However, when a tracking system is required to track a large number of targets, the computation and communication loads arise. One possible solution is to use a distributed scheme. In this paper we propose a distributed multiple target tracking algorithm, which takes into account restrictions on the sensor network functioning. Our method is based on the modification of simultaneous perturbation stochastic approximation (SPSA) algorithm with a perturbation on the input. For the proposed algorithm we get an upper bound of residual between estimates and show the simulation results. © 2018

关键词： Distributed computer systems approximation algorithms approximation theory Clutter (information theory) Optimization Sensor networks Sensor nodes State estimation stochastic systems Target tracking Communication constraints Computational constraints Distributed estimation Distributed multiple target tracking Distributed state estimation simultaneous perturbation stochastic approximation simultaneous perturbation stochastic approximation algorithms stochastic approximations

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simultaneous perturbation stochastic approximation in Decentralized Load Balancing Problem

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IFAC-PapersOnLine 2015年第11 11期48卷 936-941页

作者： Amelina, Natalia Erofeeva, Victoria Granichin, Oleg Malkovskii, Nikolai St. Petersburg Russia Institute of Problems in Mechanical Engineering Russian Academy of Sciences ITMO University St. Petersburg Russia

In this work the load balancing problem is studied for decentralized stochastic network with unknown but bounded noise in measurements and varying productivities of agents. The load balancing problem is formulated as a consensus problem in a stochastic network. Consideration of Laplasian potential function corresponded to the network graph allows to introduce a new randomized local voting protocol with constant step-size which is based on simultaneous perturbation stochastic approximation algorithm. The conditions are formulated for the approximate consensus achievement which corresponds to achieving of a suboptimal level of agents' load. The new algorithm is illustrated by simulations. © 2015

关键词： stochastic systems approximation algorithms approximation theory Multi agent systems Optimization Consensus problems Load balancing problem Randomized algorithms simultaneous perturbation stochastic approximation simultaneous perturbation stochastic approximation algorithms stochastic networks Unknown but bounded noise Varying productivity

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