Fuzzy Modeling for Control: International Series in Intelligent Technologies, cartea 12
Autor Robert Babuškaen Limba Engleză Hardback – 30 apr 1998
To automatically generate fuzzy models from measurements, a comprehensive methodology is developed which employs fuzzy clustering techniques to partition the available data into subsets characterized by locally linear behaviour. The relationships between the presented identification method and linear regression are exploited, allowing for the combination of fuzzy logic techniques with standard system identification tools. Attention is paid to the trade-off between the accuracy and transparency of the obtained fuzzy models. Control design based on a fuzzy model of a nonlinear dynamic process is addressed, using the concepts of model-based predictive control and internal model control with an inverted fuzzy model. To this end, methods to exactly invert specific types of fuzzy models are presented. In the context of predictive control, branch-and-bound optimization is applied.
The main features of the presented techniques are illustrated by means of simple examples. In addition, three real-world applications are described. Finally, software tools for building fuzzy models from measurements are available from the author.
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Paperback (1) | 1150.84 lei 6-8 săpt. | |
SPRINGER NETHERLANDS – 26 oct 2012 | 1150.84 lei 6-8 săpt. | |
Hardback (1) | 1159.34 lei 6-8 săpt. | |
SPRINGER NETHERLANDS – 30 apr 1998 | 1159.34 lei 6-8 săpt. |
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Specificații
ISBN-13: 9780792381549
ISBN-10: 0792381548
Pagini: 284
Ilustrații: XIII, 260 p.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.65 kg
Ediția:1998
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria International Series in Intelligent Technologies
Locul publicării:Dordrecht, Netherlands
ISBN-10: 0792381548
Pagini: 284
Ilustrații: XIII, 260 p.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.65 kg
Ediția:1998
Editura: SPRINGER NETHERLANDS
Colecția Springer
Seria International Series in Intelligent Technologies
Locul publicării:Dordrecht, Netherlands
Public țintă
ResearchCuprins
1. Introduction.- 2. Fuzzy Modeling.- 3. Fuzzy Clustering Algorithms.- 4. Product-Space Clustering for Identification.- 5. Constructing Fuzzy Models from Partitions.- 6. Fuzzy Models in Nonlinear Control.- 7. Applications.- Appendices.- References.- Author Index.