Identification of Fuzzy Models for Nonlinear Systems and Its Applications

Author: Liu Fucai
Publisher:
Publish Date: 2006-08-01
Features: The book elaborates on the research achievements in fuzzy model identification of nonlinear systems in recent years, covering fundamental theories and methods of fuzzy systems, various fuzzy identification methods, algorithm approximation performance analysis, and practical applications. The content includes: theoretical foundations of fuzzy modeling and fuzzy identification for nonlinear systems; analysis of the universal approximation theory of fuzzy systems; fuzzy identification of nonlinear systems based on fuzzy partition; fuzzy identification based on fuzzy clustering; fuzzy identification based on data preprocessing; the impact of membership functions on the descriptive performance of fuzzy models and the principle of fuzzy denoising; and introduces the application of fuzzy model identification with backgrounds such as hierarchical intelligent control, fuzzy model predictive control, lead-acid battery modeling for photovoltaic power stations, short-term load forecasting in power systems, and performance prediction of intelligent ceramic materials. The book is characterized by novel and extensive material, closely, reflecting the recent progress in this field. It is suitable for scientists and engineers in control science and engineering, pattern recognition and artificial intelligence, systems engineering, and management science and engineering, as well as for reference by faculty and students in related disciplines at universities.