| 书目名称 | Fuzzy Modeling for Control | | 编辑 | Robert Babuška | | 视频video | | | 丛书名称 | International Series in Intelligent Technologies | | 图书封面 |  | | 描述 | Rule-based fuzzy modeling has been recognised as a powerfultechnique for the modeling of partly-known nonlinear systems. Fuzzymodels can effectively integrate information from different sources,such as physical laws, empirical models, measurements and heuristics.Application areas of fuzzy models include prediction, decisionsupport, system analysis, control design, etc. .Fuzzy Modelingfor. .Control. addresses fuzzy modeling from the systems andcontrol engineering points of view. It focuses on the selection ofappropriate model structures, on the acquisition of dynamic fuzzymodels from process measurements (fuzzy identification), and on thedesign of nonlinear controllers based on fuzzy models. .To automatically generate fuzzy models from measurements, acomprehensive methodology is developed which employs fuzzy clusteringtechniques to partition the available data into subsets characterizedby locally linear behaviour. The relationships between the presentedidentification method and linear regression are exploited, allowingfor the combination of fuzzy logic techniques with standard systemidentification tools. Attention is paid to the trade-off between theaccuracy and transparency of the | | 出版日期 | Book 1998 | | 关键词 | addition; algorithms; modeling; optimization; set theory | | 版次 | 1 | | doi | https://doi.org/10.1007/978-94-011-4868-9 | | isbn_softcover | 978-94-010-6040-0 | | isbn_ebook | 978-94-011-4868-9Series ISSN 1382-3434 | | issn_series | 1382-3434 | | copyright | Springer Science+Business Media New York 1998 |
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