Buch, Englisch, 416 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1750 g
Reihe: Control Engineering
Buch, Englisch, 416 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1750 g
Reihe: Control Engineering
ISBN: 978-0-8176-4491-8
Verlag: Birkhäuser Boston
Fuzzy logic methodology has been proven effective in dealing with complex nonlinear systems containing uncertainties that are otherwise difficult to model. Technology based on this methodology has been applied to many real-world problems, especially in the area of consumer products. This book presents the first unified and thorough treatment of fuzzy modeling and fuzzy control, providing necessary tools for the control of complex nonlinear systems. Careful consideration is given to questions concerning model complexity, model precision, and computing time.
In addition to being an excellent reference for electrical, computer, chemical, industrial, civil, manufacturing, mechanical and aeronautical engineers, the book may also be appropriate for classroom use in a graduate course in electrical engineering, computer engineering, and computer science. Applied mathematicians, control engineers, computer scientists, and physicists will benefit from the presentation as well.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Mathematische Analysis Variationsrechnung
- Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Überwachungstechnik
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde Statik, Dynamik, Kinetik, Kinematik
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Mikroprozessoren
Weitere Infos & Material
Fuzzy Set Theory and Rough Set Theory.- Identification of the Takagi-Sugeno Fuzzy Model.- Fuzzy Model Identification Based on Rough Set Data Analysis.- Identification of the Fuzzy Hyperbolic Model.- Basic Methods of Fuzzy Inference and Control.- Fuzzy Inference and Control Methods Involving Two Kinds of Uncertainties.- Fuzzy Control Schemes via a Fuzzy Performance Evaluator.- Multivariable Predictive Control Based on the T-S Fuzzy Model.- Adaptive Control Methods Based on Fuzzy Basis Function Vectors.- Controller Design Based on the Fuzzy Hyperbolic Model.- Fuzzy H ? Filter Design for Nonlinear Discrete-Time Systems with Multiple Time-Delays.- Chaotification of the Fuzzy Hyperbolic Model.- Feedforward Fuzzy Control Approach Using the Fourier Integral.
