I. Atamanyuk, Y. Kondratenko, A. Zavgorodnii, S. Lugovoy, V. Lykhach, S. Kramarenko
{"title":"Multiparameter Stochastic Control Model Based on the Random Sequence Canonical Expansion","authors":"I. Atamanyuk, Y. Kondratenko, A. Zavgorodnii, S. Lugovoy, V. Lykhach, S. Kramarenko","doi":"10.1109/ELIT53502.2021.9501146","DOIUrl":null,"url":null,"abstract":"A stochastic mathematical model of the control system for an arbitrary number of coordinates of the object under study and control parameters is obtained. The developed mathematical model allows one to fully take into account the features of random sequences of changes of coordinates and control parameters, as well as to fully use all known a posteriori and a priori data about the control object. To obtain the model, the apparatus of nonlinear vector canonical expansions is used. The work presents diagrams that reflect the specifics of determining the parameters of a multiparameter stochastic control model and the regularities of its functioning. The obtained mathematical model has wide possibilities of practical application for solving problems of controlling objects of various nature in conditions of uncertainty.","PeriodicalId":164798,"journal":{"name":"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELIT53502.2021.9501146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A stochastic mathematical model of the control system for an arbitrary number of coordinates of the object under study and control parameters is obtained. The developed mathematical model allows one to fully take into account the features of random sequences of changes of coordinates and control parameters, as well as to fully use all known a posteriori and a priori data about the control object. To obtain the model, the apparatus of nonlinear vector canonical expansions is used. The work presents diagrams that reflect the specifics of determining the parameters of a multiparameter stochastic control model and the regularities of its functioning. The obtained mathematical model has wide possibilities of practical application for solving problems of controlling objects of various nature in conditions of uncertainty.