Genetic-Based Neurofuzzy Control for Complex Industrial Process
Author(s): Wang Yaonan, Zhang Changfan
Pages: 886-891
Year: 1999 Issue: 6
Journal: CONTROL THEORY & APPLICATIONS
Keyword: fuzzy net; learning algorithm; intelligent control;
Abstract: This paper proposes an effective fuzzy neural network controller based on genetic algorithm (GA) and supervised gradient descent learning.The fuzzy network control processing can be viewed as a parallel neural network where each neuron represents a fuzzy membership function and each link represents the weight of a fuzzy rule,and it has two important characteristics of adaptation and learning.The effectiveness of the proposed scheme is illustrated through simulation and temperature control processes.
Pages: 886-891
Year: 1999 Issue: 6
Journal: CONTROL THEORY & APPLICATIONS
Keyword: fuzzy net; learning algorithm; intelligent control;
Abstract: This paper proposes an effective fuzzy neural network controller based on genetic algorithm (GA) and supervised gradient descent learning.The fuzzy network control processing can be viewed as a parallel neural network where each neuron represents a fuzzy membership function and each link represents the weight of a fuzzy rule,and it has two important characteristics of adaptation and learning.The effectiveness of the proposed scheme is illustrated through simulation and temperature control processes.
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