Adaptive Robust Control Systems
dc.contributor.editor | Anh Tuan, Le | |
dc.date.accessioned | 2023-12-01T16:21:25Z | |
dc.date.available | 2023-12-01T16:21:25Z | |
dc.date.issued | 2018 | |
dc.identifier | ONIX_20231201_9789535137979_997 | |
dc.identifier.uri | https://directory.doabooks.org/handle/20.500.12854/129888 | |
dc.description.abstract | This 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.language | English | |
dc.subject.classification | thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TJ Electronics and communications engineering::TJF Electronics engineering::TJFM Automatic control engineering | en_US |
dc.subject.other | adaptive control, sliding mode control, machine learning, energy, neural networks, uav | |
dc.title | Adaptive Robust Control Systems | |
dc.type | book | |
oapen.identifier.doi | 10.5772/intechopen.68813 | |
oapen.relation.isPublishedBy | 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 | |
oapen.relation.isbn | 9789535137979 | |
oapen.relation.isbn | 9789535137962 | |
oapen.relation.isbn | 9789535140702 | |
oapen.imprint | IntechOpen | |
oapen.pages | 362 |
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