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dc.contributor.authorDjordjevic, Vladimir-
dc.contributor.authorFilipovic, Vojislav-
dc.date.accessioned2023-07-18T06:29:43Z-
dc.date.available2023-07-18T06:29:43Z-
dc.date.issued2014-
dc.identifier.isbn978-86-82631-74-3en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/18652-
dc.description.abstractMany industrial processes have the multivariable nature (boiler plant, evaporators, distillation columns, etc.). One of the key requests of production is energy saving and product quality improvement (these two categories are tightly connected). In order to achieve this it is necessary to carefully design process control strategies. Therefore, the quality mathematical model of the process is needed. In this paper it is assumed that the process is described with multivariable ARX (AutoRegressive model with eXogenous input) model. The key assumption, justified with numerous studies of real processes, is that the stochastic disturbance has non-Gaussian distribution. That fact affects on form of recursive identification algorithm. The algorithm becomes nonlinear. Simulations are performed that demonstrate the superiority of the proposed algorithm over the standard algorithms.en_US
dc.language.isoenen_US
dc.publisherFaculty of Mechanical and Civil Engineering, Kraljevoen_US
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.sourceVIII International Triennial Conference Heavy Machinery - HM 2014en_US
dc.subjectMultivariable systemsen_US
dc.subjectARX modelen_US
dc.subjectNon-Gaussian distributionen_US
dc.subjectRobust recursive identificationen_US
dc.titleRobust Recursive Identification of Multivariable Processesen_US
dc.typeconferenceObjecten_US
dc.description.versionPublisheden_US
dc.type.versionPublishedVersionen_US
Налази се у колекцијама:Faculty of Mechanical and Civil Engineering, Kraljevo

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