Аннотация:From the Publisher:
This book presents new approaches to the construction of fuzzy models for model-based control. New model structures and identification algorithms are described for the effective use of heterogeneous information in the form of numerical data, qualitative knowledge, and first principle models. The main methods and techniques are illustrated through several simulated examples and real-world applications from chemical and process engineering practice. Supporting MATLAB and Simulink files, available at the website www.fmt.vein.hu/softcomp, create a computational platform for exploration and illustration of many concepts and algorithms presented in the book. The book is aimed primarily at researchers, practitioners, and professionals in process control and identification, but it is also accessible to graduate students in electrical, chemical, and process engineering. Technical prerequisites include an undergraduate-level knowledge of control theory and linear algebra. Additional familiarity with fuzzy systems is helpful but not required.
