{"title":"Sensor network control based on randomized and multi-agent approaches","authors":"A. Sergeenko, O. Granichin","doi":"10.35470/2226-4116-2022-11-2-94-105","DOIUrl":null,"url":null,"abstract":"In this paper, a development of randomized and multiagent algorithms is presented. The examples and their advantages are discussed. Different combined algorithms which are applicable for the multi-sensor multitarget tracking problem are shown. These algorithms belong to the class of methods used in derivative-free optimization and has proven efficacy in the problems including significant non-statistical uncertainties. The new algorithm which is an Accelerated consensus-based SPSA algorithm is validated through simulation.The main feature of that algorithm, combining the SPSA techniques, iterative averaging (“Local Voting Protocol”) and Nesterov Acceleration Method, is the ability to solve distributed optimization problems in the presence of signals with fully uncertain distribution; the only assumption is the signal’s limitation.","PeriodicalId":37674,"journal":{"name":"Cybernetics and Physics","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cybernetics and Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35470/2226-4116-2022-11-2-94-105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Physics and Astronomy","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a development of randomized and multiagent algorithms is presented. The examples and their advantages are discussed. Different combined algorithms which are applicable for the multi-sensor multitarget tracking problem are shown. These algorithms belong to the class of methods used in derivative-free optimization and has proven efficacy in the problems including significant non-statistical uncertainties. The new algorithm which is an Accelerated consensus-based SPSA algorithm is validated through simulation.The main feature of that algorithm, combining the SPSA techniques, iterative averaging (“Local Voting Protocol”) and Nesterov Acceleration Method, is the ability to solve distributed optimization problems in the presence of signals with fully uncertain distribution; the only assumption is the signal’s limitation.
期刊介绍：
The scope of the journal includes: -Nonlinear dynamics and control -Complexity and self-organization -Control of oscillations -Control of chaos and bifurcations -Control in thermodynamics -Control of flows and turbulence -Information Physics -Cyber-physical systems -Modeling and identification of physical systems -Quantum information and control -Analysis and control of complex networks -Synchronization of systems and networks -Control of mechanical and micromechanical systems -Dynamics and control of plasma, beams, lasers, nanostructures -Applications of cybernetic methods in chemistry, biology, other natural sciences The papers in cybernetics with physical flavor as well as the papers in physics with cybernetic flavor are welcome. Cybernetics is assumed to include, in addition to control, such areas as estimation, filtering, optimization, identification, information theory, pattern recognition and other related areas.
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