Please use this identifier to cite or link to this item: http://cris.utm.md/handle/5014/1042
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dc.contributor.authorCOJUHARI, Irinaen_US
dc.contributor.authorFIODOROV Ionen_US
dc.contributor.authorIZVOREANU, Bartolomeuen_US
dc.contributor.authorMORARU, Dumitruen_US
dc.date.accessioned2021-12-08T00:34:29Z-
dc.date.available2021-12-08T00:34:29Z-
dc.date.issued2021-
dc.identifier.citationI. Cojuhari, I. Fiodorov, B. Izvoreanu and D. Moraru, "Synthesis of the State-Feedback Controllers by the Genetic Algorithm According to the Maximum Stability Degree Criterion," 2021 23rd International Conference on Control Systems and Computer Science (CSCS), 2021, pp. 83-88, doi: 10.1109/CSCS52396.2021.00021.en_US
dc.identifier.isbn978-1-6654-3939-8-
dc.identifier.isbn978-1-6654-3940-4-
dc.identifier.issn2379-0482-
dc.identifier.issn2379-0474-
dc.identifier.urihttp://cris.utm.md/handle/5014/1042-
dc.description.abstractThe synthesis algorithm of state-feedback controllers is proposed in this paper. It was improved the procedure of finding the tuning parameters by the maximum stability degree criterion, using the genetic algorithm. Based on the genetic algorithm it is calculated the value of the maximum stability degree, according to witch it is calculated the control vector of the state-feedback controller. The proposed algorithm was verified by the computer simulation and there are presented some case studies. The case study was done for the situation when the control object is approximated with model of object with inertia and inertia with astatism.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation20.80009.5007.26. Modele, algoritmi şi tehnologii de conducere, optimizare şi securizare a sistemelor Ciber- Fiziceen_US
dc.relation.ispartof2021 23rd International Conference on Control Systems and Computer Science (CSCS)en_US
dc.subjectautomatic control systemen_US
dc.subjectmaximum stability degreeen_US
dc.subjectstate-feedback controllersen_US
dc.subjectgenetic algorithmen_US
dc.titleSynthesis of the State-Feedback Controllers by the Genetic Algorithm According to the Maximum Stability Degree Criterionen_US
dc.typeArticleen_US
dc.relation.conferenceCSCSen_US
dc.identifier.doi10.1109/CSCS52396.2021.00021-
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.languageiso639-1other-
crisitem.project.grantno20.80009.5007.26-
crisitem.project.fundingProgramState Programme-
crisitem.author.deptDepartment of Software Engineering and Automatics-
crisitem.author.deptDepartment of Software Engineering and Automatics-
crisitem.author.deptDepartment of Software Engineering and Automatics-
crisitem.author.deptDepartment of Software Engineering and Automatics-
crisitem.author.parentorgFaculty of Computers, Informatics and Microelectronics-
crisitem.author.parentorgFaculty of Computers, Informatics and Microelectronics-
crisitem.author.parentorgFaculty of Computers, Informatics and Microelectronics-
crisitem.author.parentorgFaculty of Computers, Informatics and Microelectronics-
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