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Vision‐Guided Flame Control Using Fuzzy Logic and Neural Networks
Author(s) -
Tao Wenjing,
Burkhardt Hans
Publication year - 1995
Publication title -
particle and particle systems characterization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.877
H-Index - 56
eISSN - 1521-4117
pISSN - 0934-0866
DOI - 10.1002/ppsc.19950120207
Subject(s) - fuzzy logic , artificial neural network , computer science , process (computing) , fuzzy control system , artificial intelligence , neuro fuzzy , control (management) , control engineering , machine learning , engineering , operating system
This paper presents an application of fuzzy and neural network techniques to a vision‐guided closed loop control for stationary luminous flames. The image processing technique is used to analyze and identify the process states. Fuzzy control strategy avoids the difficulty in establishing a mathematical model for an ill‐defined process. Expert knowledge and training patterns can be incorporated into fuzzy rules, which are represented in the form of neurons. The use of a neural network makes it easy to increase the number of control parameters and provides the system the possibility to adjust its performance automatically.