Title: Techniques and Applications of Integrated Neural Network-Based Fuzzy Logic Control Systems
Abstract: This chapter discusses the techniques and applications of integrated neural network based fuzzy logic control systems. A fuzzy system consists of a bunch of fuzzy if-then rules. The chapter presents a neural fuzzy inference network, SONFIN, with online self-constructing capability. The SONFIN is a general connectionist model of a fuzzy logic system, which can find its optimal structure and parameters automatically. Both the structure and parameter identification schemes are performed simultaneously during online learning, so the SONFIN can be used for normal operation at any time as learning proceeds without any assignment of fuzzy rules in advance. One important task in the structural identification of a neural fuzzy network is the partition of the input space, which influences the number of fuzzy rules generated. A novel network construction method for solving the dilemma between the number of rules and the number of consequent terms is developed. The number of generated rules and membership functions is small, even for modeling a sophisticated system. This chapter also discusses that the SONFIN is applied to the temperature control of the rapid thermal processing (RTF) system.
Publication Year: 1999
Publication Date: 1999-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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Cited By Count: 7
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