Language identification of controlled systems: Modelling, control and anomaly detection

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dc.creatorMartins, J. F.
dc.creatorDente, J. A.
dc.creatorPires, A. J.
dc.creatorMendes, R. Vilela
dc.date2000-07-25
dc.date.accessioned2026-07-07T03:16:24Z
dc.date.available2026-07-07T03:16:24Z
dc.descriptionFormal language techniques have been used in the past to study autonomous dynamical systems. However, for controlled systems, new features are needed to distinguish between information generated by the system and input control. We show how the modelling framework for controlled dynamical systems leads naturally to a formulation in terms of context-dependent grammars. A learning algorithm is proposed for on-line generation of the grammar productions, this formulation being then used for modelling, control and anomaly detection. Practical applications are described for electromechanical drives. Grammatical interpolation techniques yield accurate results and the pattern detection capabilities of the language-based formulation makes it a promising technique for the early detection of anomalies or faulty behaviour.
dc.description27 pages Latex, 18 figures
dc.identifierhttps://arxiv.org/abs/cs/0007036
dc.identifierhttp://arxiv.org/abs/cs/0007036
dc.identifierIEEE Trans. in Systems, Man and Cybernetics 31 (2001) 234
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30341
dc.subjectComputation and Language
dc.subjectI.2.8
dc.titleLanguage identification of controlled systems: Modelling, control and anomaly detection
dc.typetext

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