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dc.contributor.editorAnh Tuan, Le
dc.date.accessioned2023-12-01T16:21:25Z
dc.date.available2023-12-01T16:21:25Z
dc.date.issued2018
dc.identifierONIX_20231201_9789535137979_997
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/129888
dc.description.abstractThis book focuses on the applications of robust and adaptive control approaches to practical systems. The proposed control systems hold two important features: (1) The system is robust with the variation in plant parameters and disturbances (2) The system adapts to parametric uncertainties even in the unknown plant structure by self-training and self-estimating the unknown factors. The various kinds of robust adaptive controls represented in this book are composed of sliding mode control, model-reference adaptive control, gain-scheduling, H-infinity, model-predictive control, fuzzy logic, neural networks, machine learning, and so on. The control objects are very abundant, from cranes, aircrafts, and wind turbines to automobile, medical and sport machines, combustion engines, and electrical machines.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineeringen_US
dc.subject.otheradaptive control, sliding mode control, machine learning, energy, neural networks, uav
dc.titleAdaptive Robust Control Systems
dc.typebook
oapen.identifier.doi10.5772/intechopen.68813
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9789535137979
oapen.relation.isbn9789535137962
oapen.relation.isbn9789535140702
oapen.imprintIntechOpen
oapen.pages362


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